What’s new¶
This topic describes new functionality and breaking changes for recently released versions of Epidemiological MODeling software (EMOD).
Contents
EMOD v2.20¶
The EMOD v2.20 release includes support for typhoid disease modeling, including new campaign classes: EnvironmentalDiagnostic, TyphoidCarrierDiagnostic, TyphoidVaccine, and TyphoidWASH.
ImmunityBloodTest was added for identifying whether an individual’s immunity meets a specified threshold and then broadcasts an event based on the results. This new campaign class can be used with all supported disease modeling sim types.
InterventionForCurrentPartners can be used with STI and HIV sim types and provides a mechanism for the partners of individuals in the care system to also seek care.
OutbreakIndividualTBorHIV extends OutbreakIndividual and allows for specifying HIV or a specific strain of infection for TB.
In addition, configuration and campaign parameters that set the type of distribution (uniform, Gaussian, etc.) of infectiousness, incubation period, and delivery of interventions have been refactored. The number of distributions available and naming conventions used are now consistent across the configuration and campaign files. This change does not affect the distributions used in the demographics files.
A beta release of new campaign classes (not yet fully tested) are included to support surveillance of events, where events are listened to, detected, and broadcast when a threshold has been met. These classes include: BroadcastCoordinatorEvent, BroadcastNodeEvent, DelayEventCoordinator, SurveillanceEventCoordinator, and TriggeredEventCoordinator.
New configuration parameters (Distribution)¶
Note: These configuration parameters are part of the refactoring of distribution parameters.
New configuration parameters (Beta)¶
Note: These configuration parameters are currently in beta release and have not yet been fully tested.
New demographics parameters¶
In all simulation types, you can now specify the quantity-per-timestep added to the total infectivity present in a node; it is equivalent to the expected number of additional infections in a node, per timestep. For example, if timestep is equal to a day, then setting InfectivityReservoirSize to a value of 0.1 would introduce an infection every 10 days from the exogenous reservoir.
For more information, see the table below.
Parameter |
Data type |
Minimum |
Maximum |
Default |
Description |
Example |
|---|---|---|---|---|---|---|
InfectivityReservoirEndTime |
float |
InfectivityReservoirStartTime |
3.40E+38 |
3.40E+38 |
The ending of the exogeneous reservoir of infectivity. This parameter is conditional upon the configuration parameter, Enable_Infectivity_Reservoir, being enabled (set to 1). |
{
"NodeAttributes": {
"InfectivityReservoirSize": 0.1,
"InfectivityReservoirStartTime": 90,
"InfectivityReservoirEndTime": 365
}
}
|
InfectivityReservoirSize |
float |
0 |
3.40E+38 |
0 |
The quantity-per-timestep added to the total infectivity present in a node; it is equivalent to the expected number of additional infections in a node, per timestep. For example, if timestep is equal to a day, then setting InfectivityReservoirSize to a value of 0.1 would introduce an infection every 10 days from the exogenous reservoir. This parameter is conditional upon the configuration parameter, Enable_Infectivity_Reservoir, being enabled (set to 1). |
{
"NodeAttributes": {
"InfectivityReservoirSize": 0.1,
"InfectivityReservoirStartTime": 90,
"InfectivityReservoirEndTime": 365
}
}
|
InfectivityReservoirStartTime |
float |
0 |
3.40E+38 |
0 |
The beginning of the exogeneous reservoir of infectivity. This parameter is conditional upon the configuration parameter, Enable_Infectivity_Reservoir, being enabled (set to 1). |
{
"NodeAttributes": {
"InfectivityReservoirSize": 0.1,
"InfectivityReservoirStartTime": 90,
"InfectivityReservoirEndTime": 365
}
}
|
New campaign parameters¶
The following campaign classes are new and can be used in the (specified) models:
ImmunityBloodTest (generic)¶
The ImmunityBloodTest intervention class identifies whether an individual’s immunity meets a specified threshold (as set with the Positive_Threshold_AcquisitionImmunity campaign parameter) and then broadcasts an event based on the results; positive has immunity while negative does not.
Parameter |
Data type |
Minimum |
Maximum |
Default |
Description |
Example |
|---|---|---|---|---|---|---|
Base_Sensitivity |
float |
0 |
1 |
1 |
The sensitivity of the diagnostic. This sets the proportion of the time that individuals with the condition being tested receive a positive diagnostic test. When set to zero, then individuals who have the condition always receive a false-negative diagnostic test. |
{
"Event_Coordinator_Config": {
"Demographic_Coverage": 1,
"Intervention_Config": {
"Base_Sensitivity": 1,
"Base_Specificity": 1,
"Cost_To_Consumer": 0,
"Days_To_Diagnosis": 0,
"Event_Or_Config": "Event",
"Positive_Diagnosis_Event": "TestedPositive_IamImmune",
"Negative_Diagnosis_Event": "TestedNegative_IamSusceptible",
"Treatment_Fraction": 1,
"Positive_Threshold_AcquisitionImmunity": 0.99,
"class": "ImmunityBloodTest"
}
}
}
|
Base_Specificity |
float |
0 |
1 |
1 |
The specificity of the diagnostic. This sets the proportion of the time that individuals without the condition being tested receive a negative diagnostic test. When set to 1, the diagnostic always accurately reflects the lack of having the condition. When set to zero, then individuals who do not have the condition always receive a false-positive diagnostic test. |
{
"Event_Coordinator_Config": {
"Demographic_Coverage": 1,
"Intervention_Config": {
"Base_Sensitivity": 1,
"Base_Specificity": 1,
"Cost_To_Consumer": 0,
"Days_To_Diagnosis": 0,
"Event_Or_Config": "Event",
"Negative_Diagnosis_Event": "TestedNegative_IamSusceptible",
"Positive_Diagnosis_Event": "TestedPositive_IamImmune",
"Positive_Threshold_AcquisitionImmunity": 0.99,
"Treatment_Fraction": 1,
"class": "ImmunityBloodTest"
}
}
}
|
Cost_To_Consumer |
float |
0 |
3.40282e+38 |
1 |
The unit ‘cost’ assigned to the diagnostic. Setting Cost_To_Consumer to zero for all other interventions, and to a non-zero amount for one intervention, provides a convenient way to track the number of times the intervention has been applied in a simulation. |
{
"Event_Coordinator_Config": {
"Demographic_Coverage": 1,
"Intervention_Config": {
"Base_Sensitivity": 1,
"Base_Specificity": 1,
"Cost_To_Consumer": 0,
"Days_To_Diagnosis": 0,
"Event_Or_Config": "Event",
"Negative_Diagnosis_Event": "TestedNegative_IamSusceptible",
"Positive_Diagnosis_Event": "TestedPositive_IamImmune",
"Positive_Threshold_AcquisitionImmunity": 0.99,
"Treatment_Fraction": 1,
"class": "ImmunityBloodTest"
}
}
}
|
Days_To_Diagnosis |
float |
0 |
3.40282e+38 |
0 |
The number of days from test until diagnosis. |
{
"Event_Coordinator_Config": {
"Demographic_Coverage": 1,
"Intervention_Config": {
"Base_Sensitivity": 1,
"Base_Specificity": 1,
"Cost_To_Consumer": 0,
"Days_To_Diagnosis": 0,
"Event_Or_Config": "Event",
"Negative_Diagnosis_Event": "TestedNegative_IamSusceptible",
"Positive_Diagnosis_Event": "TestedPositive_IamImmune",
"Positive_Threshold_AcquisitionImmunity": 0.99,
"Treatment_Fraction": 1,
"class": "ImmunityBloodTest"
}
}
}
|
Disqualifying_Properties |
array of strings |
NA |
NA |
[] |
A list of IndividualProperty key:value pairs that cause an intervention to be aborted. Generally used to control the flow of health care access. For example, to prevent the same individual from accessing health care via two different routes at the same time. |
{
"Event_Coordinator_Config": {
"Demographic_Coverage": 1,
"Intervention_Config": {
"Base_Sensitivity": 1,
"Base_Specificity": 1,
"Cost_To_Consumer": 0,
"Days_To_Diagnosis": 0,
"Disqualifying_Properties": [
"InterventionStatus:LostForever"
],
"Event_Or_Config": "Event",
"Negative_Diagnosis_Event": "TestedNegative_IamSusceptible",
"Positive_Diagnosis_Event": "TestedPositive_IamImmune",
"Positive_Threshold_AcquisitionImmunity": 0.99,
"Treatment_Fraction": 1,
"class": "ImmunityBloodTest"
}
}
}
|
Dont_Allow_Duplicates |
boolean |
0 |
1 |
0 |
If an individual’s container has an intervention, set to true (1) to prevent them from receiving another copy of the intervention. Supported by all intervention classes. |
{
"Event_Coordinator_Config": {
"Demographic_Coverage": 1,
"Intervention_Config": {
"Base_Sensitivity": 1,
"Base_Specificity": 1,
"Cost_To_Consumer": 0,
"Days_To_Diagnosis": 0,
"Dont_Allow_Duplicates": 0,
"Event_Or_Config": "Event",
"Negative_Diagnosis_Event": "TestedNegative_IamSusceptible",
"Positive_Diagnosis_Event": "TestedPositive_IamImmune",
"Positive_Threshold_AcquisitionImmunity": 0.99,
"Treatment_Fraction": 1,
"class": "ImmunityBloodTest"
}
}
}
|
Enable_IsSymptomatic |
boolean |
0 |
1 |
0 |
If true (1), requires an infection to be symptomatic to return a positive test. |
{
"Enable_IsSymptomatic": 1,
"Base_Specificity": 0.85,
"Base_Sensitivity": 0.92
}
|
Intervention_Name |
string |
NA |
NA |
NA |
The optional name used to refer to this intervention as a means to differentiate it from others that use the same class. |
{
"Event_Coordinator_Config": {
"Demographic_Coverage": 1,
"Intervention_Config": {
"Base_Sensitivity": 1,
"Base_Specificity": 1,
"Cost_To_Consumer": 0,
"Days_To_Diagnosis": 0,
"Event_Or_Config": "Event",
"Intervention_Name": "Immunity Blood Test - Series 1",
"Negative_Diagnosis_Event": "TestedNegative_IamSusceptible",
"Positive_Diagnosis_Event": "TestedPositive_IamImmune",
"Positive_Threshold_AcquisitionImmunity": 0.99,
"Treatment_Fraction": 1,
"class": "ImmunityBloodTest"
}
}
}
|
Negative_Diagnosis_Event |
enum |
NA |
NA |
“” |
If an individual tests negative (does not have immunity), then an individual type event is broadcast. This may trigger another intervention when the event occurs. Only used when Event_Or_Config is set to Event. |
{
"Event_Coordinator_Config": {
"Demographic_Coverage": 1,
"Intervention_Config": {
"Base_Sensitivity": 1,
"Base_Specificity": 1,
"Cost_To_Consumer": 0,
"Days_To_Diagnosis": 0,
"Event_Or_Config": "Event",
"Negative_Diagnosis_Event": "TestedNegative_IamSusceptible",
"Positive_Diagnosis_Event": "TestedPositive_IamImmune",
"Positive_Threshold_AcquisitionImmunity": 0.99,
"Treatment_Fraction": 1,
"class": "ImmunityBloodTest"
}
}
}
|
New_Property_Value |
string |
NA |
NA |
NA |
An optional IndividualProperty key:value pair that will be assigned when the intervention is distributed. Generally used to indicate the broad category of health care cascade to which an intervention belongs to prevent individuals from accessing care through multiple pathways. |
{
"New_Property_Value": "InterventionStatus:None"
}
|
Positive_Diagnosis_Config |
JSON object |
NA |
NA |
NA |
The intervention distributed to individuals if they test positive. Only used when Event_Or_Config is set to Config. |
{
"Event_Coordinator_Config": {
"Demographic_Coverage": 1,
"Intervention_Config": {
"Base_Sensitivity": 1,
"Base_Specificity": 1,
"Cost_To_Consumer": 0,
"Days_To_Diagnosis": 0,
"Event_Or_Config": "Event",
"Negative_Diagnosis_Event": "TestedNegative_IamSusceptible",
"Positive_Diagnosis_Event": "TestedPositive_IamImmune",
"Positive_Threshold_AcquisitionImmunity": 0.99,
"Treatment_Fraction": 1,
"class": "ImmunityBloodTest"
}
}
}
|
Positive_Diagnosis_Event |
enum |
NA |
NA |
“” |
If the test is positive (has immunity), then an individual type event is broadcast. This may trigger another intervention when the event occurs. Only used if Event_Or_Config is set to Event. |
{
"Event_Coordinator_Config": {
"Demographic_Coverage": 1,
"Intervention_Config": {
"Base_Sensitivity": 1,
"Base_Specificity": 1,
"Cost_To_Consumer": 0,
"Days_To_Diagnosis": 0,
"Event_Or_Config": "Event",
"Negative_Diagnosis_Event": "TestedNegative_IamSusceptible",
"Positive_Diagnosis_Event": "TestedPositive_IamImmune",
"Positive_Threshold_AcquisitionImmunity": 0.99,
"Treatment_Fraction": 1,
"class": "ImmunityBloodTest"
}
}
}
|
Positive_Threshold_AcquisitionImmunity |
float |
0 |
1 |
1 |
Specifies the threshold for acquired immunity, where 1 equals 100% immunity and 0 equals 100% susceptible. |
{
"Event_Coordinator_Config": {
"Demographic_Coverage": 1,
"Intervention_Config": {
"Base_Sensitivity": 1,
"Base_Specificity": 1,
"Cost_To_Consumer": 0,
"Days_To_Diagnosis": 0,
"Event_Or_Config": "Event",
"Negative_Diagnosis_Event": "TestedNegative_IamSusceptible",
"Positive_Diagnosis_Event": "TestedPositive_IamImmune",
"Positive_Threshold_AcquisitionImmunity": 0.99,
"Treatment_Fraction": 1,
"class": "ImmunityBloodTest"
}
}
}
|
Treatment_Fraction |
float |
0 |
1 |
1 |
The fraction of positive diagnoses that are treated. |
{
"Event_Coordinator_Config": {
"Demographic_Coverage": 1,
"Intervention_Config": {
"Base_Sensitivity": 1,
"Base_Specificity": 1,
"Cost_To_Consumer": 0,
"Days_To_Diagnosis": 0,
"Event_Or_Config": "Event",
"Negative_Diagnosis_Event": "TestedNegative_IamSusceptible",
"Positive_Diagnosis_Event": "TestedPositive_IamImmune",
"Positive_Threshold_AcquisitionImmunity": 0.99,
"Treatment_Fraction": 1,
"class": "ImmunityBloodTest"
}
}
}
|
InterventionForCurrentPartners (HIV, STI)¶
The InterventionForCurrentPartners intervention class provides a mechanism for the partners of individuals in the care system to also seek care. Partners do not need to seek testing at the same time; a delay may occur between the initial test and the partner’s test. If a relationship has been paused, such as when a partner migrates to a different node, the partner will not be contacted.
Parameter |
Data type |
Minimum |
Maximum |
Default |
Description |
Example |
|---|---|---|---|---|---|---|
Broadcast_Event |
string |
NA |
NA |
“” |
The event that is immediately broadcast to the partner. Required if Event_or_Config is set to Event. See Event list for possible built-in values, or create custom values using Custom_Individual_Events. |
{
"Broadcast_Event": "HIVNewlyDiagnosed"
}
|
Disqualifying_Properties |
array of strings |
NA |
NA |
A list of IndividualProperty key:value pairs that cause an intervention to be aborted (persistent interventions will stop being distributed to individuals with these values). See NodeProperties and IndividualProperties parameters for more information. Generally used to control the flow of health care access. For example, to prevent the same individual from accessing health care via two different routes at the same time. |
{
"Disqualifying_Properties": [
"InterventionStatus:LostForever"
]
}
|
|
Dont_Allow_Duplicates |
boolean |
0 |
1 |
0 |
If an individual’s container has an intervention, set to true (1) to prevent them from receiving another copy of the intervention. Supported by all intervention classes. |
{
"Dont_Allow_Duplicates": 0
}
|
Event_Or_Config |
enum |
NA |
NA |
Config |
Specifies whether the current intervention (or a positive diagnosis, depending on the intervention class) distributes a nested intervention (the Config option) or an event will be broadcast which may trigger other interventions in the campaign file (the Event option). Possible values are:
|
{
"Event_Or_Config": "Event"
}
|
Intervention_Config |
JSON object |
The intervention definition that is immediately distributed to the partner. Required if Event_Or_Config is set to Config. |
{
"class": "StandardInterventionDistributionEventCoordinator",
"Intervention_Config": {
"class": "NodeLevelHealthTriggeredIV",
"Trigger_Condition_List": [
"Some_Other_Event"
],
"Actual_IndividualIntervention_Config": {
"class": "InterventionForCurrentPartners",
"Disqualifying_Properties": [],
"New_Property_Value": "CascadeState:TestingCurrentPartner",
"Relationship_Types": [
"MARITAL",
"INFORMAL",
"TRANSITORY",
"COMMERCIAL"
],
"Minimum_Duration_Years": 0.5,
"Prioritize_Partners_By": "LONGER_TIME_IN_RELATIONSHIP",
"Maximum_Partners": 2,
"Event_Or_Config": "Event",
"Broadcast_Event": "HIVNewlyDiagnosed"
}
}
}
|
|||
Intervention_Name |
string |
NA |
NA |
InterventionForCurrentPartners |
The optional name used to refer to this intervention as a means to differentiate it from others that use the same class. |
{
"Intervention_Config": {
"Intervention_Name": "Intervention_For_Spouse",
"class": "InterventionForCurrentPartnersr"
}
}
|
Maximum_Partners |
integer |
0 |
1000 |
100 |
The maximum number of partners that will receive the intervention. Required when Prioritize_Partners_By is not set to NO_PRIORITIZATION. |
{
"Prioritize_Partners_By": "NO_PRIORITIZATION",
"Maximum_Partners": 2
}
|
Minimum_Duration_Years |
float |
0 |
200 |
0 |
The minimum amount of time, in years, between relationship formation and the current time for the partner to qualify for the intervention. |
{
"Minimum_Duration_Years": 0.5
}
|
New_Property_Value |
string |
NA |
NA |
An optional IndividualProperty key:value pair that will be assigned when the intervention is distributed. See NodeProperties and IndividualProperties parameters for more information. Generally used to indicate the broad category of health care cascade to which an intervention belongs to prevent individuals from accessing care through multiple pathways. For example, if an individual must already be taking a particular medication to be prescribed a new one. |
{
"New_Property_Value": "InterventionStatus:None"
}
|
|
Prioritize_Partners_By |
enum |
NA |
NA |
NO_PRIORITIZATION |
How to prioritize partners for the intervention, as long as they have been in a relationship longer than Minimum_Duration_Years. Possible values are:
|
{
"Prioritize_Partners_By": "LONGER_TIME_IN_RELATIONSHIP"
}
|
Relationship_Types |
array of strings |
NA |
NA |
NA |
An array listing all possible relationship types for which partners can qualify for the intervention. Supported partnerships include TRANSITORY, INFORMAL, MARITAL, and COMMERCIAL. If Prioritize_Partners_By is set to RELATIONSHIP_TYPE, then the order of these types is used. The array may not contain duplicates, and cannot be empty. |
{
"Relationship_Types": [
"MARITAL",
"INFORMAL",
"TRANSITORY",
"COMMERCIAL"
]
}
|
OutbreakIndividualTBorHIV (tuberculosis)¶
The OutbreakIndividualTBorHIV class extends OutbreakIndividual class and allows for specifying HIV or a specific strain of infection for TB.
Parameter |
Data type |
Minimum |
Maximum |
Default |
Description |
Example |
|---|---|---|---|---|---|---|
Antigen |
integer |
0 |
10 |
0 |
The antigenic base strain ID of the outbreak infection. This must not exceed the number specified in the configuration parameter Number_Basestrains. |
{
"Intervention_Config": {
"Antigen": 0,
"Genome": 0,
"Infection_Type": "TB",
"Outbreak_Source": "PrevalenceIncrease",
"class": "OutbreakIndividualTBorHIV"
}
}
|
Genome |
integer |
-1 |
16777200 |
0 |
The genetic substrain ID of the outbreak infection. This must not exceed the number specified in the configuration parameter Number_Substrains. |
{
"Intervention_Config": {
"Antigen": 0,
"Genome": 0,
"Infection_Type": "TB",
"Outbreak_Source": "PrevalenceIncrease",
"class": "OutbreakIndividualTBorHIV"
}
}
|
Ignore_Immunity |
boolean |
0 |
1 |
1 |
Individuals will be force-infected (with a specific strain) regardless of actual immunity level when set to true (1). |
{
"Intervention_Config": {
"Antigen": 0,
"Genome": 0,
"Infection_Type": "TB",
"Outbreak_Source": "PrevalenceIncrease",
"Ignore_Immunity": 0,
"class": "OutbreakIndividualTBorHIV"
}
}
|
Incubation_Period_Override |
integer |
-1 |
2147480000 |
-1 |
The incubation period, in days, that infected individuals will go through before becoming infectious. This value overrides the incubation period set in the configuration file. Set to -1 to honor the configuration parameter settings. |
{
"Intervention_Config": {
"Antigen": 0,
"Genome": 0,
"Ignore_Immunity": 0,
"Incubation_Period_Override": -1,
"Infection_Type": "TB",
"Outbreak_Source": "PrevalenceIncrease",
"class": "OutbreakIndividualTBorHIV"
}
}
|
Infection_Type |
enum |
NA |
NA |
HIV |
Infection type. Possible values are:
|
{
"Intervention_Config": {
"Antigen": 0,
"Genome": 0,
"Ignore_Immunity": 0,
"Incubation_Period_Override": -1,
"Infection_Type": "TB",
"Outbreak_Source": "PrevalenceIncrease",
"class": "OutbreakIndividualTBorHIV"
}
}
|
EnvironmentalDiagnostic (typhoid)¶
The EnvironmentalDiagnostic intervention class identifies contaminated locations by sampling the environment, comparing the value to a threshold, and broadcasting either a positive or negative node event.
Parameter |
Data type |
Minimum |
Maximum |
Default |
Description |
Example |
|---|---|---|---|---|---|---|
Base_Sensitivity |
float |
0 |
1 |
1 |
The likelihood that a positive measurement was made. If the contagion measurement is greater than the Sample_Threshold, a random number is drawn to determine if the detection was actually made. |
{
"Base_Sensitivity": 0.7,
"Sample_Threshold": 0.85
}
|
Base_Specificity |
float |
0 |
1 |
1 |
The proportion of time that the environment being tested and without the condition receives a negative diagnostic test. When set to 1, the diagnostic always accurately reflects the lack of having the condition. When set to zero, then environments that do not have the condition always receive a false-positive diagnostic test. |
{
"Base_Specificity": 0.9
}
|
Disqualifying_Properties |
array of strings |
NA |
NA |
NA |
A list of NodeProperty key:value pairs that cause an intervention to be aborted (persistent interventions will stop being distributed to nodes with these values). See NodeProperties and IndividualProperties parameters for more information. Generally used to control the flow of health care access. For example, to prevent the same individual from accessing health care via two different routes at the same time. |
{
"Disqualifying_Properties": []
}
|
Environment_IP_Key_Value |
string |
NA |
NA |
NA |
An IndividualProperty key:value pair that indicates a specific transmission pool, typically used to identify a location. If none is provided, the sample will be taken on the entire node. |
{
"Environment_IP_Key_Value": "Location:UP_RIVER"
}
|
Intervention_Name |
string |
NA |
NA |
EnvironmentalDiagnostic |
The optional name used to refer to this intervention as a means to differentiate it from others that use the same class. |
{
"Intervention_Config": {
"Intervention_Name": "Downriver sample testing",
"class": "EnvironmentalDiagnostic"
}
}
|
Negative_Diagnostic_Event |
string |
NA |
NA |
“” |
The event that will be broadcast to the node when the sample value is less than the threshold (e.g. the test is negative). If this is an empty string or set to NoTrigger, no event will be broadcast. See Event list for possible values, or create custom events using Custom_Node_Events. |
{
"Event_Or_Config": "Event",
"Negative_Diagnostic_Event": "Up_River_Clean"
}
|
New_Property_Value |
string |
NA |
NA |
NA |
An optional NodeProperty key:value pair that will be assigned when the intervention is distributed. See NodeProperties and IndividualProperties parameters for more information. Generally used to indicate the broad category of health care cascade to which an intervention belongs to prevent individuals from accessing care through multiple pathways. For example, if an individual must already be taking a particular medication to be prescribed a new one. |
{
"New_Property_Value": "InterventionStatus:None"
}
|
Positive_Diagnostic_Event |
string |
NA |
NA |
“” |
The event that will be broadcast to the node when the sample value is greater than the threshold (e.g. the test is positive). This cannot be an empty string or set to NoTrigger. See Event list for possible values, or create custom events using Custom_Node_Events. |
{
"Positive_Diagnostic_Event": "Up_River_Contagion_Found"
}
|
Sample_Threshold |
float |
0 |
3.40282e+38 |
0 |
The threshold that delineates a positive versus negative sampling result. If the sample is greater than the threshold, a positive finding will result; if the value is less than the threshold, it will be negative. This does not include values equal to the threshold so that the threshold can be set to zero; if the threshold is zero, the test is simply looking for any deposit in the transmission pool. |
{
"Sample_Threshold": 0.2
}
|
TyphoidCarrierDiagnostic (typhoid)¶
The TyphoidCarrierDiagnostic class extends SimpleDiagnostic class and allows for positive test diagnostic when an individual is a chronic typhoid carrier.
Parameter |
Data type |
Minimum |
Maximum |
Default |
Description |
Example |
|---|---|---|---|---|---|---|
Base_Sensitivity |
float |
0 |
1 |
1 |
The sensitivity of the diagnostic. This sets the proportion of the time that individuals with the condition being tested receive a positive diagnostic test. When set to zero, then individuals who have the condition always receive a false-negative diagnostic test. |
{
"Base_Sensitivity": 1
}
|
Base_Specificity |
float |
0 |
1 |
1 |
The specificity of the diagnostic. This sets the proportion of the time that individuals without the condition being tested receive a negative diagnostic test. When set to 1, the diagnostic always accurately reflects the lack of having the condition. When set to zero, then individuals who do not have the condition always receive a false-positive diagnostic test. |
{
"Base_Specificity": 1
}
|
Cost_To_Consumer |
float |
0 |
3.40282e+38 |
1 |
The unit ‘cost’ assigned to the diagnostic. Setting Cost_To_Consumer to zero for all other interventions, and to a non-zero amount for one intervention, provides a convenient way to track the number of times the intervention has been applied in a simulation. |
{
"Cost_To_Consumer": 10
}
|
Days_To_Diagnosis |
float |
0 |
3.40282e+38 |
0 |
The number of days from test until diagnosis. |
{
"Days_To_Diagnosis": 2
}
|
Disqualifying_Properties |
array of strings |
NA |
NA |
[] |
A list of IndividualProperty key:value pairs that cause an intervention to be aborted (persistent interventions will stop being distributed to individuals with these values). See NodeProperties and IndividualProperties parameters for more information. Generally used to control the flow of health care access. For example, to prevent the same individual from accessing health care via two different routes at the same time. |
{
"Disqualifying_Properties": [
"InterventionStatus:LostForever"
]
}
|
Dont_Allow_Duplicates |
boolean |
0 |
1 |
0 |
If an individual’s container has an intervention, set to true (1) to prevent them from receiving another copy of the intervention. Supported by all intervention classes. |
{
"Dont_Allow_Duplicates": 0
}
|
Enable_IsSymptomatic |
boolean |
0 |
1 |
0 |
If true (1), requires an infection to be symptomatic to return a positive test. |
{
"Base_Sensitivity": 0.92,
"Base_Specificity": 0.85,
"Enable_IsSymptomatic": 1
}
|
Event_Or_Config |
enum |
NA |
NA |
Config |
Specifies whether the current intervention (or a positive diagnosis, depending on the intervention class) distributes a nested intervention (the Config option) or an event will be broadcast which may trigger other interventions in the campaign file (the Event option). Possible values are:
|
{
"Event_Or_Config": "Config"
}
|
Intervention_Name |
string |
NA |
NA |
NA |
The optional name used to refer to this intervention as a means to differentiate it from others that use the same class. |
{
"Intervention_Config": {
"Intervention_Name": "Typhoid diagnostic test",
"class": "TyphoidCarrierDiagnostic"
}
}
|
New_Property_Value |
string |
NA |
NA |
NA |
An optional IndividualProperty key:value pair that will be assigned when the intervention is distributed. See NodeProperties and IndividualProperties parameters for more information. Generally used to indicate the broad category of health care cascade to which an intervention belongs to prevent individuals from accessing care through multiple pathways. For example, if an individual must already be taking a particular medication to be prescribed a new one. |
{
"New_Property_Value": "InterventionStatus:None"
}
|
Positive_Diagnosis_Config |
JSON object |
NA |
NA |
NA |
The intervention distributed to individuals if they test positive. Only used when Event_Or_Config is set to Config. |
{
"Event_Coordinator_Config": {
"Intervention_Config": {
"class": "TyphoidCarrierDiagnostic",
"Event_Or_Config": "Event",
"Positive_Diagnosis_Event": "Chronic_Carrier"
},
"Number_Repetitions": 10,
"Timesteps_Between_Repetitions": 180,
"class": "StandardInterventionDistributionEventCoordinator"
},
"Event_Name": "Diagnostic",
"Nodeset_Config": {
"class": "NodeSetAll"
},
"Start_Day": 2,
"Target_Demographic": "Everyone",
"class": "CampaignEvent"
}
|
Positive_Diagnosis_Event |
enum |
NA |
NA |
“” |
If the test is positive, this specifies an event that can trigger another intervention when the event occurs. Only used if Event_Or_Config is set to Event. See Event list for possible values, or create custom events using Custom_Individual_Events. |
{
"Event_Coordinator_Config": {
"Intervention_Config": {
"class": "TyphoidCarrierDiagnostic",
"Event_Or_Config": "Event",
"Positive_Diagnosis_Event": "Chronic_Carrier"
},
"Number_Repetitions": 10,
"Timesteps_Between_Repetitions": 180,
"class": "StandardInterventionDistributionEventCoordinator"
},
"Event_Name": "Diagnostic",
"Nodeset_Config": {
"class": "NodeSetAll"
},
"Start_Day": 2,
"Target_Demographic": "Everyone",
"class": "CampaignEvent"
}
|
Treatment_Fraction |
float |
0 |
1 |
1 |
The fraction of positive diagnoses that are treated. |
{
"Treatment_Fraction": 1
}
|
TyphoidVaccine (typhoid)¶
The TyphoidVaccine intervention class identifies contaminated locations by sampling the environment, comparing the value to a threshold, and broadcasting either a positive or negative node event.
Parameter |
Data type |
Minimum |
Maximum |
Default |
Description |
Example |
|---|---|---|---|---|---|---|
Changing_Effect |
JSON object |
NA |
NA |
NA |
A highly configurable effect that changes over time. Specify how this effect decays over time using one of the Waning effect classes. |
{
"Intervention_Config": {
"Changing_Effect": {
"Durability_Map": {
"Times": [
0,
10,
11,
20,
21,
26,
27,
33,
34,
40
],
"Values": [
0,
0,
1,
1,
0,
0,
1,
1,
0,
0
]
},
"Expire_At_Durability_Map_End": 1,
"Initial_Effect": 1,
"class": "WaningEffectMapLinear"
},
"Effect": 1,
"Mode": "Dose",
"Target_Demographic": "Everyone",
"class": "TyphoidVaccine"
}
}
|
Disqualifying_Properties |
array of strings |
NA |
NA |
[] |
A list of IndividualProperty key:value pairs that cause an intervention to be aborted (persistent interventions will stop being distributed to individuals with these values). See NodeProperties and IndividualProperties parameters for more information. Generally used to control the flow of health care access. For example, to prevent the same individual from accessing health care via two different routes at the same time. |
{
"Disqualifying_Properties": [
"InterventionStatus:LostForever"
]
}
|
Dont_Allow_Duplicates |
boolean |
0 |
1 |
0 |
If an individual’s container has an intervention, set to true (1) to prevent them from receiving another copy of the intervention. Supported by all intervention classes. |
{
"Dont_Allow_Duplicates": 0
}
|
Effect |
float |
0 |
1 |
1 |
The efficacy of the Typhoid vaccine intervention. For example, a value of 1 would be 100 percent efficacy for all targeted nodes within the intervention. |
{
"Intervention_Config": {
"Changing_Effect": {
"Durability_Map": {
"Times": [
0,
10,
11,
20,
21,
26,
27,
33,
34,
40
],
"Values": [
0,
0,
1,
1,
0,
0,
1,
1,
0,
0
]
},
"Expire_At_Durability_Map_End": 1,
"Initial_Effect": 1,
"class": "WaningEffectMapLinear"
},
"Effect": 1,
"Mode": "Dose",
"Target_Demographic": "Everyone",
"class": "TyphoidVaccine"
}
}
|
Intervention_Name |
string |
NA |
NA |
NA |
The optional name used to refer to this intervention as a means to differentiate it from others that use the same class. |
{
"Intervention_Config": {
"class": "TyphoidVaccine",
"Intervention_Name": "Country-wide vaccination campaign"
}
}
|
Mode |
enum |
NA |
NA |
Shedding |
The mode of contact transmission of typhoid targeted by the intervention. Possible values are:
|
{
"Intervention_Config": {
"Changing_Effect": {
"Durability_Map": {
"Times": [
0,
10,
11,
20,
21,
26,
27,
33,
34,
40
],
"Values": [
0,
0,
1,
1,
0,
0,
1,
1,
0,
0
]
},
"Expire_At_Durability_Map_End": 1,
"Initial_Effect": 1,
"class": "WaningEffectMapLinear"
},
"Effect": 1,
"Mode": "Dose",
"Target_Demographic": "Everyone",
"class": "TyphoidVaccine"
}
}
|
New_Property_Value |
string |
NA |
NA |
NA |
An optional IndividualProperty key:value pair that will be assigned when the intervention is distributed. See NodeProperties and IndividualProperties parameters for more information. Generally used to indicate the broad category of health care cascade to which an intervention belongs to prevent individuals from accessing care through multiple pathways. For example, if an individual must already be taking a particular medication to be prescribed a new one. |
{
"New_Property_Value": "InterventionStatus:None"
}
|
TyphoidWASH (typhoid)¶
The TyphoidWASH intervention class acts on exposure through either the contact contagion population or the environmental contagion population in the simulation. The intervention can be configured to reduce either exposure dose or exposure frequency for each route, simulating effects of water, sanitation, and hygiene (WASH) interventions.
Parameter |
Data type |
Minimum |
Maximum |
Default |
Description |
Example |
|---|---|---|---|---|---|---|
Changing_Effect |
JSON object |
NA |
NA |
NA |
A highly configurable effect that changes over time. Specify how this effect decays over time using one of the Waning effect classes. |
{
"Intervention_Config": {
"Changing_Effect": {
"Expire_At_Durability_Map_End": 1,
"Initial_Effect": 1,
"class": "WaningEffectConstant"
},
"Effect": 1,
"Mode": "Exposures",
"Use_Property_Targeting": 0,
"class": "TyphoidWASH"
}
}
|
Disqualifying_Properties |
array of strings |
NA |
NA |
[] |
A list of IndividualProperty key:value pairs that cause an intervention to be aborted (persistent interventions will stop being distributed to individuals with these values). See NodeProperties and IndividualProperties parameters for more information. Generally used to control the flow of health care access. For example, to prevent the same individual from accessing health care via two different routes at the same time. |
{
"Disqualifying_Properties": [
"InterventionStatus:LostForever"
]
}
|
Effect |
float |
0 |
1 |
1 |
The efficacy of the TyphoidWASH intervention. For example, a value of 1 would be 100 percent efficacy for all targeted nodes within the intervention. |
{
"Intervention_Config": {
"Changing_Effect": {
"Expire_At_Durability_Map_End": 1,
"Initial_Effect": 1,
"class": "WaningEffectConstant"
},
"Effect": 1,
"Mode": "Exposures",
"Use_Property_Targeting": 0,
"class": "TyphoidWASH"
}
}
|
Intervention_Name |
string |
NA |
NA |
NA |
The optional name used to refer to this intervention as a means to differentiate it from others that use the same class. |
{
"Intervention_Config": {
"Intervention_Name": "TyphoidWASH intervention campaign",
"class": "TyphoidWASH"
}
}
|
Mode |
enum |
NA |
NA |
Shedding |
The mode of environmental or contact transmission of typhoid targeted by the intervention. Possible values are:
|
{
"Intervention_Config": {
"Mode": "Exposures",
"Effect": 1,
"Use_Property_Targeting": 0,
"Changing_Effect": {
"class": "WaningEffectConstant",
"Initial_Effect": 1,
"Expire_At_Durability_Map_End": 1
},
"class": "TyphoidWASH"
}
}
|
New_Property_Value |
string |
NA |
NA |
NA |
An optional NodeProperty key:value pair that will be assigned when the intervention is distributed. See NodeProperties and IndividualProperties parameters for more information. Generally used to indicate the broad category of health care cascade to which an intervention belongs to prevent individuals from accessing care through multiple pathways. For example, if an individual must already be taking a particular medication to be prescribed a new one. |
{
"New_Property_Value": "InterventionStatus:None"
}
|
Targeted_Individual_Properties |
string |
NA |
NA |
NA |
Individual Property key-value pairs to be targeted (optional). |
{
"Intervention_Config": {
"Mode": "Exposures",
"Effect": 1,
"Use_Property_Targeting": 1,
"Changing_Effect": {
"class": "WaningEffectMapLinear",
"Initial_Effect": 1,
"Expire_At_Durability_Map_End": 1,
"Durability_Map": {
"Times": [
0,
100,
200,
300,
400,
500
],
"Values": [
0,
1,
1,
1,
0,
1
]
}
},
"class": "TyphoidWASH",
"Targeted_Individual_Properties": "Risk:Target_Demographic"
}
}
|
Use_Property_Targeting |
boolean |
0 |
1 |
1 |
Set to 1 (true) – or omit – if you want to use the Targeted_Individual_Property parameter to limit the effect of this intervention to just certain individuals. Set to 0 to apply effect to everyone. |
{
"Event_Coordinator_Config": {
"Intervention_Config": {
"Mode": "Shedding",
"Use_Property_Targeting": 0,
"Effect": 1.0,
"Changing_Effect": {
"class": "WaningEffectConstant",
"Initial_Effect": 1.0,
"Expire_At_Durability_Map_End": 1
},
"class": "TyphoidWASH"
},
"class": "StandardInterventionDistributionEventCoordinator"
},
"Nodeset_Config": {
"class": "NodeSetAll"
},
"Start_Day": 10,
"class": "CampaignEvent"
}
|
New campaign parameters (Beta)¶
Note
These campaign classes and associated parameters are currently in beta release and have not yet been fully tested.
BroadcastCoordinatorEvent (generic)¶
The BroadcastCoordinatorEvent coordinator class broadcasts the event you specify. This can be used with the campaign class, SurveillanceEventCoordinator, that can monitor and listen for events received from BroadcastCoordinatorEvent and then perform an action based on the broadcasted event. You can also use this for the reporting of the broadcasted events by setting the configuraton parameters, Report_Node_Event_Recorder and Report_Surveillance_Event_Recorder, which listen to events to be recorded.
Parameter |
Data type |
Minimum |
Maximum |
Default |
Description |
Example |
|---|---|---|---|---|---|---|
Broadcast_Event |
string |
NA |
NA |
“” |
The name of the event to be broadcast. This event must be set in the Custom_Coordinator_Events configuration parameter. This cannot be assigned an empty string for the event. |
{
"class": "CampaignEvent",
"Start_Day": 5,
"Nodeset_Config": {
"class": "NodeSetAll"
},
"Event_Coordinator_Config": {
"class": "BroadcastCoordinatorEvent",
"Coordinator_Name": "Coordnator_1",
"Cost_To_Consumer": 10,
"Broadcast_Event": "Coordinator_Event_1"
}
}
|
Coordinator_Name |
string |
NA |
NA |
NA |
The unique identifying coordinator name, which is useful with the output report, ReportCoordinatorEventRecorder.csv. |
{
"class": "CampaignEvent",
"Start_Day": 25,
"Nodeset_Config": {
"class": "NodeSetAll"
},
"Event_Coordinator_Config": {
"class": "BroadcastCoordinatorEvent",
"Coordinator_Name": "Coordinator_3",
"Cost_To_Consumer": 30,
"Broadcast_Event": "Coordinator_Event_3"
}
}
|
Cost_To_Consumer |
float |
0 |
3.40282e+38 |
0 |
The unit cost of broadcasting the event. |
{
"class": "CampaignEvent",
"Start_Day": 15,
"Nodeset_Config": {
"class": "NodeSetAll"
},
"Event_Coordinator_Config": {
"class": "BroadcastCoordinatorEvent",
"Coordinator_Name": "Coordnator_2",
"Cost_To_Consumer": 20,
"Broadcast_Event": "Coordinator_Event_2"
}
}
|
BroadcastNodeEvent (generic)¶
The BroadcastNodeEvent coordinator class broadcasts node events. This can be used with the campaign class, SurveillanceEventCoordinator, that can monitor and listen for events received from BroadcastNodeEvent and then perform an action based on the broadcasted event. You can also use this for the reporting of the broadcasted events by setting the configuraton parameters, Report_Node_Event_Recorder and Report_Surveillance_Event_Recorder, which listen to events to be recorded.
Parameter |
Data type |
Minimum |
Maximum |
Default |
Description |
Example |
|---|---|---|---|---|---|---|
Broadcast_Event |
string |
NA |
NA |
“” |
The name of the node event to broadcast. This event must be set in the Custom_Node_Events configuration parameter. |
{
"class": "CampaignEvent",
"Start_Day": 5,
"Nodeset_Config": {
"class": "NodeSetNodeList",
"Node_List": [
1
]
},
"Event_Coordinator_Config": {
"class": "StandardInterventionDistributionEventCoordinator",
"Intervention_Config": {
"class": "BroadcastNodeEvent",
"Cost_To_Consumer": 10,
"Broadcast_Event": "Node_Event_1"
}
}
}
|
Cost_To_Consumer |
float |
0 |
999999 |
0 |
The unit cost of the intervention campaign that will be assigned to the specified nodes, as configured under Nodeset_Config. |
{
"class": "CampaignEvent",
"Start_Day": 5,
"Nodeset_Config": {
"class": "NodeSetNodeList",
"Node_List": [
1
]
},
"Event_Coordinator_Config": {
"class": "StandardInterventionDistributionEventCoordinator",
"Intervention_Config": {
"class": "BroadcastNodeEvent",
"Cost_To_Consumer": 10,
"Broadcast_Event": "Node_Event_1"
}
}
}
|
DelayEventCoordinator (generic)¶
The DelayEventCoordinator coordinator class insert delays into coordinator event chains. This campaign event is typically used with BroadcastCoordinatorEvent to broadcast events after the delays.
Parameter |
Data type |
Minimum |
Maximum |
Default |
Description |
Example |
|---|---|---|---|---|---|---|
Coordinator_Name |
string |
NA |
NA |
DelayEventCoordinator |
The unique identifying coordinator name, which is useful with the output report, ReportCoordinatorEventRecorder.csv. |
{
"Event_Coordinator_Config": {
"Coordinator_Name": "DelayEventCoordinator_10",
"Delay_Complete_Event": "Completion_Delayed_Coordinator_Event_1",
"Delay_Period_Distribution": "FIXED_DURATION",
"Delay_Period_Fixed": 25,
"Duration": 100,
"Start_Trigger_Condition_List": [
"Coordinator_Event_1"
],
"Stop_Trigger_Condition_List": [],
"class": "DelayEventCoordinator"
},
"Event_Name": "Delay",
"Nodeset_Config": {
"class": "NodeSetAll"
},
"Start_Day": 1,
"Target_Demographic": "Everyone",
"class": "CampaignEvent",
"comment": "Delay"
}
|
Delay_Complete_Event |
string |
NA |
NA |
NA |
The delay completion event to be included in the ReportCoordinatorEventRecorder.csv output report, upon completion of the delay period. |
{
"Event_Coordinator_Config": {
"Coordinator_Name": "DelayEventCoordinator_10",
"Delay_Complete_Event": "Completion_Delayed_Coordinator_Event_1",
"Delay_Distribution": "GAUSSIAN_DURATION",
"Delay_Period_Mean": 25,
"Delay_Period_Std_Dev": 5,
"Duration": 100,
"Start_Trigger_Condition_List": [
"Coordinator_Event_1"
],
"Stop_Trigger_Condition_List": [],
"class": "DelayEventCoordinator"
},
"Event_Name": "Delay",
"Nodeset_Config": {
"class": "NodeSetAll"
},
"Start_Day": 1,
"Target_Demographic": "Everyone",
"class": "CampaignEvent",
"comment": "Delay"
}
|
Delay_Period_Constant |
float |
0 |
3.40282E+38 |
6 |
The delay period to use for all interventions when Delay_Period_Distribution is set to CONSTANT_DISTRIBUTION. |
{
"Delay_Period_Distribution": "CONSTANT_DISTRIBUTION",
"Delay_Period_Constant": 8
}
|
Delay_Period_Distribution |
enum |
NA |
NA |
NOT_INITIALIZED |
The distribution type to use for assigning the delay period for distributing interventions. Each assigned value is a random draw from the distribution. Possible values are:
|
{
"Delay_Period_Distribution": "GAUSSIAN_DISTRIBUTION",
"Delay_Period_Gaussian_Mean": 8,
"Delay_Period_Gaussian_Std_Dev": 1.5
}
|
Delay_Period_Exponential |
float |
0 |
3.40282E+38 |
6 |
The mean of the delay period when Delay_Period_Distribution is set to EXPONENTIAL_DISTRIBUTION. |
{
"Delay_Period_Distribution": "EXPONENTIAL_DISTRIBUTION",
"Delay_Period_Exponential": 4.25
}
|
Delay_Period_Gaussian_Mean |
float |
0 |
3.40282E+38 |
6 |
The mean of the delay period when Delay_Period_Distribution is set to GAUSSIAN_DISTRIBUTION. |
{
"Delay_Period_Distribution": "GAUSSIAN_DISTRIBUTION",
"Delay_Period_Gaussian_Mean": 8,
"Delay_Period_Gaussian_Std_Dev": 1.5
}
|
Delay_Period_Gaussian_Std_Dev |
float |
1.17549E-38 |
3.40282E+38 |
1 |
The standard deviation of the delay period when Delay_Period_Distribution is set to GAUSSIAN_DISTRIBUTION. |
{
"Delay_Period_Distribution": "GAUSSIAN_DISTRIBUTION",
"Delay_Period_Gaussian_Mean": 8,
"Delay_Period_Gaussian_Std_Dev": 1.5
}
|
Delay_Period_Kappa |
float |
1.17549E-38 |
3.40282E+38 |
1 |
The shape value for the delay period when Delay_Period_Distribution is set to WEIBULL_DISTRIBUTION. |
{
"Delay_Period_Distribution": "WEIBULL_DISTRIBUTION",
"Delay_Period_Kappa": 0.9,
"Delay_Period_Lambda": 1.5
}
|
Delay_Period_Lambda |
float |
1.17549E-38 |
3.40282E+38 |
1 |
The scale value for the delay period when Delay_Period_Distribution is set to WEIBULL_DISTRIBUTION. |
{
"Delay_Period_Distribution": "WEIBULL_DISTRIBUTION",
"Delay_Period_Kappa": 0.9,
"Delay_Period_Lambda": 1.5
}
|
Delay_Period_Log_Normal_Mu |
float |
-3.40282e+38 |
3.40282E+38 |
6 |
The mean of the natural log of the delay period when Delay_Period_Distribution is set to LOG_NORMAL_DISTRIBUTION. |
{
"Delay_Period_Distribution": "LOG_NORMAL_DISTRIBUTION",
"Delay_Period_Log_Normal_Mu": 9,
"Delay_Period_Log_Normal_Sigma": 2
}
|
Delay_Period_Log_Normal_Sigma |
float |
-3.40282e+38 |
3.40282E+38 |
1 |
The standard deviation of the natural log of the delay period when Delay_Period_Distribution is set to LOG_NORMAL_DISTRIBUTION. |
{
"Delay_Period_Distribution": "LOG_NORMAL_DISTRIBUTION",
"Delay_Period_Log_Normal_Mu": 9,
"Delay_Period_Log_Normal_Sigma": 2
}
|
Delay_Period_Max |
float |
0 |
3.40282E+38 |
1 |
The maximum delay period when Delay_Period_Distribution is set to UNIFORM_DISTRIBUTION. |
{
"Delay_Period_Distribution": "UNIFORM_DISTRIBUTION",
"Delay_Period_Min": 2,
"Delay_Period_Max": 7
}
|
Delay_Period_Mean_1 |
float |
1.17549E-38 |
3.40282E+38 |
1 |
The mean of the first exponential distribution when Delay_Period_Distribution is set to DUAL_EXPONENTIAL_DISTRIBUTION. |
{
"Delay_Period_Distribution": "DUAL_EXPONENTIAL_DISTRIBUTION",
"Delay_Period_Mean_1": 4,
"Delay_Period_Mean_2": 12,
"Delay_Period_Proportion_1": 0.2
}
|
Delay_Period_Mean_2 |
float |
1.17549E-38 |
3.40282E+38 |
1 |
The mean of the second exponential distribution when Delay_Period_Distribution is set to DUAL_EXPONENTIAL_DISTRIBUTION. |
{
"Delay_Period_Distribution": "DUAL_EXPONENTIAL_DISTRIBUTION",
"Delay_Period_Mean_1": 4,
"Delay_Period_Mean_2": 12,
"Delay_Period_Proportion_1": 0.2
}
|
Delay_Period_Min |
float |
0 |
3.40282E+38 |
0 |
The minimum delay period when Delay_Period_Distribution is set to UNIFORM_DISTRIBUTION. |
{
"Delay_Period_Distribution": "UNIFORM_DISTRIBUTION",
"Delay_Period_Min": 2,
"Delay_Period_Max": 7
}
|
Delay_Period_Peak_2_Value |
float |
0 |
3.40282E+38 |
1 |
The delay period value to assign to the remaining interventions when Delay_Period_Distribution is set to DUAL_CONSTANT_DISTRIBUTION. |
{
"Delay_Period_Distribution": "DUAL_CONSTANT_DISTRIBUTION",
"Delay_Period_Proportion_0": 0.25,
"Delay_Period_Peak_2_Value": 5
}
|
Delay_Period_Poisson_Mean |
float |
0 |
3.40282E+38 |
6 |
The mean of the delay period when Delay_Period_Distribution is set to POISSON_DISTRIBUTION. |
{
"Delay_Period_Distribution": "POISSON_DISTRIBUTION",
"Delay_Period_Poisson_Mean": 5
}
|
Delay_Period_Proportion_0 |
float |
0 |
1 |
1 |
The proportion of interventions to assign a value of zero delay when Delay_Period_Distribution is set to DUAL_CONSTANT_DISTRIBUTION. |
{
"Delay_Period_Distribution": "DUAL_CONSTANT_DISTRIBUTION",
"Delay_Period_Proportion_0": 0.25,
"Delay_Period_Peak_2_Value": 5
}
|
Delay_Period_Proportion_1 |
float |
0 |
1 |
1 |
The proportion of interventions in the first exponential distribution when Delay_Period_Distribution is set to DUAL_EXPONENTIAL_DISTRIBUTION. |
{
"Delay_Period_Distribution": "DUAL_EXPONENTIAL_DISTRIBUTION",
"Delay_Period_Mean_1": 4,
"Delay_Period_Mean_2": 12,
"Delay_Period_Proportion_1": 0.2
}
|
Duration |
float |
-1 |
3.40282e+38 |
-1 |
The number of days from when the delay event coordinator was created by the campaign event. Once the number of days has passed, the delay event coordinator will unregister for events and expire. The default value of ‘-1’ = never expire. |
{
"Event_Coordinator_Config": {
"Coordinator_Name": "DelayEventCoordinator_10",
"Delay_Complete_Event": "Completion_Delayed_Coordinator_Event_1",
"Delay_Period_Distribution": "FIXED_DURATION",
"Delay_Period_Fixed": 25,
"Duration": 100,
"Start_Trigger_Condition_List": [
"Coordinator_Event_1"
],
"Stop_Trigger_Condition_List": [],
"class": "DelayEventCoordinator"
},
"Event_Name": "Delay",
"Nodeset_Config": {
"class": "NodeSetAll"
},
"Start_Day": 1,
"Target_Demographic": "Everyone",
"class": "CampaignEvent"
}
|
Start_Trigger_Condition_List |
array of strings |
NA |
NA |
NA |
The start trigger event condition list contains events defined in the Custom_Coordinator_Events config parameter that will trigger to start a new delay. If the delay event coordinator has already been triggered and is currently waiting for the duration of a delay, it will then ignore a new delay event. The list cannot be empty. |
{
"Event_Coordinator_Config": {
"Coordinator_Name": "DelayEventCoordinator_10",
"Delay_Complete_Event": "Completion_Delayed_Coordinator_Event_1",
"Delay_Period_Distribution": "FIXED_DURATION",
"Delay_Period_Fixed": 25,
"Duration": 100,
"Start_Trigger_Condition_List": [
"Coordinator_Event_1"
],
"Stop_Trigger_Condition_List": [],
"class": "DelayEventCoordinator"
},
"Event_Name": "Delay",
"Nodeset_Config": {
"class": "NodeSetAll"
},
"Start_Day": 1,
"Target_Demographic": "Everyone",
"class": "CampaignEvent",
"comment": "Delay"
}
|
Stop_Trigger_Condition_List |
array of strings |
NA |
NA |
NA |
The stop trigger event condition list contains events defined in the Custom_Coordinator_Events config parameter that will trigger to stop a delay period, but does not stop the delay event coordinator. The event is not broadcast. |
{
"Event_Coordinator_Config": {
"Coordinator_Name": "DelayEventCoordinator_10",
"Delay_Complete_Event": "Completion_Delayed_Coordinator_Event_1",
"Delay_Period_Distribution": "FIXED_DURATION",
"Delay_Period_Fixed": 25,
"Duration": 100,
"Start_Trigger_Condition_List": [
"Coordinator_Event_1"
],
"Stop_Trigger_Condition_List": [],
"class": "DelayEventCoordinator"
},
"Event_Name": "Delay",
"Nodeset_Config": {
"class": "NodeSetAll"
},
"Start_Day": 1,
"Target_Demographic": "Everyone",
"class": "CampaignEvent",
"comment": "Delay"
}
|
SurveillanceEventCoordinator (generic)¶
The SurveillanceEventCoordinator coordinator class listens for and detects events happening and then responds with broadcasted events when a threshold has been met. This campaign event is typically used with other classes, such as BroadcastCoordinatorEvent, TriggeredEventCoordinator, and DelayEventCoordinator.
Parameter |
Data type |
Minimum |
Maximum |
Default |
Description |
Example |
|---|---|---|---|---|---|---|
Action_List |
array of JSON objects |
NA |
NA |
NA |
A list of possible actions to take if a particular threshold is met. An action is taken when the specified threshold value is less than the number of incidence counted. If there are multiple actions listed then the action with the highest threshold value, that is also less than the number of incidence counted, is selected. The list cannot be empty. |
{
"Event_Coordinator_Config": {
"Coordinator_Name": "ACF_Counter",
"Duration": 30,
"Incidence_Counter": {
"Counter_Event_Type": "NODE",
"Counter_Period": 14,
"Counter_Type": "PERIODIC",
"Demographic_Coverage": 1,
"Target_Demographic": "Everyone",
"Trigger_Condition_List": [
"Node_Event_1",
"Node_Event_2"
]
},
"Responder": {
"Action_List": [
{
"Event_To_Broadcast": "Ind_Start_SIA_2",
"Event_Type": "COORDINATOR",
"Threshold": 5
},
{
"Event_To_Broadcast": "Ind_Start_SIA_4",
"Event_Type": "COORDINATOR",
"Threshold": 2
}
],
"Responded_Event": "Respond_To_Surveillance",
"Threshold_Type": "COUNT"
},
"Start_Trigger_Condition_List": [
"Start_ACF"
],
"Stop_Trigger_Condition_List": [
"Start_SIA_2",
"Start_SIA_4"
],
"class": "SurveillanceEventCoordinator"
},
"Nodeset_Config": {
"class": "NodeSetAll"
},
"Start_Day": 1,
"class": "CampaignEvent"
}
|
Coordinator_Name |
string |
NA |
NA |
TriggeredEventCoordinator |
The unique identifying coordinator name, which is useful with the output report, ReportSurveillanceEventRecorder.csv. |
{
"class": "CampaignEvent",
"Start_Day": 1,
"Nodeset_Config": {
"class": "NodeSetAll"
},
"Event_Coordinator_Config": {
"class": "SurveillanceEventCoordinator",
"Coordinator_Name": "ACF_Counter",
"Start_Trigger_Condition_List": [
"Start_ACF"
],
"Stop_Trigger_Condition_List": [
"Start_SIA_2",
"Start_SIA_4"
],
"Duration": 30,
"Incidence_Counter": {
"Counter_Type": "PERIODIC",
"Counter_Period": 14,
"Counter_Event_Type": "NODE",
"Trigger_Condition_List": [
"Node_Event_1",
"Node_Event_2"
],
"Target_Demographic": "Everyone",
"Demographic_Coverage": 1
},
"Responder": {
"Responded_Event": "Respond_To_Surveillance",
"Threshold_Type": "COUNT",
"Action_List": [
{
"Threshold": 5,
"Event_Type": "COORDINATOR",
"Event_To_Broadcast": "Ind_Start_SIA_2"
},
{
"Threshold": 2,
"Event_Type": "COORDINATOR",
"Event_To_Broadcast": "Ind_Start_SIA_4"
}
]
}
}
}
|
Counter_Event_Type |
enum |
NA |
NA |
INDIVIDUAL |
Type of events that can be included in Trigger_Condition_List. Possible values are:
|
{
"Event_Coordinator_Config": {
"Coordinator_Name": "ACF_Counter",
"Duration": 30,
"Incidence_Counter": {
"Counter_Event_Type": "NODE",
"Counter_Period": 14,
"Counter_Type": "PERIODIC",
"Demographic_Coverage": 1,
"Target_Demographic": "Everyone",
"Trigger_Condition_List": [
"Node_Event_1",
"Node_Event_2"
]
},
"Responder": {
"Action_List": [
{
"Event_To_Broadcast": "Ind_Start_SIA_2",
"Event_Type": "COORDINATOR",
"Threshold": 5
},
{
"Event_To_Broadcast": "Ind_Start_SIA_4",
"Event_Type": "COORDINATOR",
"Threshold": 2
}
],
"Responded_Event": "Respond_To_Surveillance",
"Threshold_Type": "COUNT"
},
"Start_Trigger_Condition_List": [
"Start_ACF"
],
"Stop_Trigger_Condition_List": [
"Start_SIA_2",
"Start_SIA_4"
],
"class": "SurveillanceEventCoordinator"
},
"Nodeset_Config": {
"class": "NodeSetAll"
},
"Start_Day": 1,
"class": "CampaignEvent"
}
|
Counter_Period |
float |
1 |
10000 |
1 |
When Counter_Type is set to PERIODIC, this is the counter period (in days). |
{
"Event_Coordinator_Config": {
"Coordinator_Name": "ACF_Counter",
"Duration": 30,
"Incidence_Counter": {
"Counter_Event_Type": "NODE",
"Counter_Period": 14,
"Counter_Type": "PERIODIC",
"Demographic_Coverage": 1,
"Target_Demographic": "Everyone",
"Trigger_Condition_List": [
"Node_Event_1",
"Node_Event_2"
]
},
"Responder": {
"Action_List": [
{
"Event_To_Broadcast": "Ind_Start_SIA_2",
"Event_Type": "COORDINATOR",
"Threshold": 5
},
{
"Event_To_Broadcast": "Ind_Start_SIA_4",
"Event_Type": "COORDINATOR",
"Threshold": 2
}
],
"Responded_Event": "Respond_To_Surveillance",
"Threshold_Type": "COUNT"
},
"Start_Trigger_Condition_List": [
"Start_ACF"
],
"Stop_Trigger_Condition_List": [
"Start_SIA_2",
"Start_SIA_4"
],
"class": "SurveillanceEventCoordinator"
},
"Nodeset_Config": {
"class": "NodeSetAll"
},
"Start_Day": 1,
"class": "CampaignEvent"
}
|
Counter_Type |
enum |
NA |
NA |
PERIODIC |
Counter type used for surveillance of events. The counter is triggered by events in Start_Trigger_Condition_List and the counter stops when it receives an event in Stop_Trigger_Condition_List or the listening duration expires. Possible values are:
|
{
"Event_Coordinator_Config": {
"Coordinator_Name": "ACF_Counter",
"Duration": 30,
"Incidence_Counter": {
"Counter_Event_Type": "NODE",
"Counter_Period": 14,
"Counter_Type": "PERIODIC",
"Demographic_Coverage": 1,
"Target_Demographic": "Everyone",
"Trigger_Condition_List": [
"Node_Event_1",
"Node_Event_2"
]
},
"Responder": {
"Action_List": [
{
"Event_To_Broadcast": "Ind_Start_SIA_2",
"Event_Type": "COORDINATOR",
"Threshold": 5
},
{
"Event_To_Broadcast": "Ind_Start_SIA_4",
"Event_Type": "COORDINATOR",
"Threshold": 2
}
],
"Responded_Event": "Respond_To_Surveillance",
"Threshold_Type": "COUNT"
},
"Start_Trigger_Condition_List": [
"Start_ACF"
],
"Stop_Trigger_Condition_List": [
"Start_SIA_2",
"Start_SIA_4"
],
"class": "SurveillanceEventCoordinator"
},
"Nodeset_Config": {
"class": "NodeSetAll"
},
"Start_Day": 1,
"class": "CampaignEvent"
}
|
Demographic_Coverage |
float |
0 |
1 |
1 |
The fraction of individuals in the target demographic that are counted. |
{
"Event_Coordinator_Config": {
"Coordinator_Name": "ACF_Counter",
"Duration": 30,
"Incidence_Counter": {
"Counter_Event_Type": "NODE",
"Counter_Period": 14,
"Counter_Type": "PERIODIC",
"Demographic_Coverage": 1,
"Target_Demographic": "Everyone",
"Trigger_Condition_List": [
"Node_Event_1",
"Node_Event_2"
]
},
"Responder": {
"Action_List": [
{
"Event_To_Broadcast": "Ind_Start_SIA_2",
"Event_Type": "COORDINATOR",
"Threshold": 5
},
{
"Event_To_Broadcast": "Ind_Start_SIA_4",
"Event_Type": "COORDINATOR",
"Threshold": 2
}
],
"Responded_Event": "Respond_To_Surveillance",
"Threshold_Type": "COUNT"
},
"Start_Trigger_Condition_List": [
"Start_ACF"
],
"Stop_Trigger_Condition_List": [
"Start_SIA_2",
"Start_SIA_4"
],
"class": "SurveillanceEventCoordinator"
},
"Nodeset_Config": {
"class": "NodeSetAll"
},
"Start_Day": 1,
"class": "CampaignEvent"
}
|
Duration |
float |
-1 |
3.40282e+38 |
-1 |
The number of days from when the surveillance event coordinator was created by the campaign event. Once the number of days has passed, the delay event coordinator will unregister for events and expire. The default value of ‘-1’ = never expire. |
{
"Event_Coordinator_Config": {
"Coordinator_Name": "ACF_Counter",
"Duration": 30,
"Incidence_Counter": {
"Counter_Event_Type": "NODE",
"Counter_Period": 14,
"Counter_Type": "PERIODIC",
"Demographic_Coverage": 1,
"Target_Demographic": "Everyone",
"Trigger_Condition_List": [
"Node_Event_1",
"Node_Event_2"
]
},
"Responder": {
"Action_List": [
{
"Event_To_Broadcast": "Ind_Start_SIA_2",
"Event_Type": "COORDINATOR",
"Threshold": 5
},
{
"Event_To_Broadcast": "Ind_Start_SIA_4",
"Event_Type": "COORDINATOR",
"Threshold": 2
}
],
"Responded_Event": "Respond_To_Surveillance",
"Threshold_Type": "COUNT"
},
"Start_Trigger_Condition_List": [
"Start_ACF"
],
"Stop_Trigger_Condition_List": [
"Start_SIA_2",
"Start_SIA_4"
],
"class": "SurveillanceEventCoordinator"
},
"Nodeset_Config": {
"class": "NodeSetAll"
},
"Start_Day": 1,
"class": "CampaignEvent"
}
|
Event_Type |
enum |
NA |
NA |
INDIVIDUAL |
The type of event to be broadcast. Possible values are:
|
{
"Event_Coordinator_Config": {
"Coordinator_Name": "ACF_Counter",
"Duration": 30,
"Incidence_Counter": {
"Counter_Event_Type": "NODE",
"Counter_Period": 14,
"Counter_Type": "PERIODIC",
"Demographic_Coverage": 1,
"Target_Demographic": "Everyone",
"Trigger_Condition_List": [
"Node_Event_1",
"Node_Event_2"
]
},
"Responder": {
"Action_List": [
{
"Event_To_Broadcast": "Ind_Start_SIA_2",
"Event_Type": "COORDINATOR",
"Threshold": 5
},
{
"Event_To_Broadcast": "Ind_Start_SIA_4",
"Event_Type": "COORDINATOR",
"Threshold": 2
}
],
"Responded_Event": "Respond_To_Surveillance",
"Threshold_Type": "COUNT"
},
"Start_Trigger_Condition_List": [
"Start_ACF"
],
"Stop_Trigger_Condition_List": [
"Start_SIA_2",
"Start_SIA_4"
],
"class": "SurveillanceEventCoordinator"
},
"Nodeset_Config": {
"class": "NodeSetAll"
},
"Start_Day": 1,
"class": "CampaignEvent"
}
|
Incidence_Counter |
array of JSON objects |
NA |
NA |
NA |
List of JSON objects for specifying the conditions and parameters that must be met for an incidence to be counted. Some of the values are specified in the following parameters: Counter_Type, Counter_Period, Counter_Event_Type, Trigger_Condition_List, Node_Property_Restrictions, Property_Restrictions_Within_Node. |
{
"Event_Coordinator_Config": {
"Coordinator_Name": "ACF_Counter",
"Duration": 30,
"Incidence_Counter": {
"Counter_Event_Type": "NODE",
"Counter_Period": 14,
"Counter_Type": "PERIODIC",
"Demographic_Coverage": 1,
"Target_Demographic": "Everyone",
"Trigger_Condition_List": [
"Node_Event_1",
"Node_Event_2"
]
},
"Responder": {
"Action_List": [
{
"Event_To_Broadcast": "Ind_Start_SIA_2",
"Event_Type": "COORDINATOR",
"Threshold": 5
},
{
"Event_To_Broadcast": "Ind_Start_SIA_4",
"Event_Type": "COORDINATOR",
"Threshold": 2
}
],
"Responded_Event": "Respond_To_Surveillance",
"Threshold_Type": "COUNT"
},
"Start_Trigger_Condition_List": [
"Start_ACF"
],
"Stop_Trigger_Condition_List": [
"Start_SIA_2",
"Start_SIA_4"
],
"class": "SurveillanceEventCoordinator"
},
"Nodeset_Config": {
"class": "NodeSetAll"
},
"Start_Day": 1,
"class": "CampaignEvent"
}
|
Node_Property_Restrictions |
array of JSON objects |
NA |
NA |
NA |
A list of the NodeProperty key:value pairs, as defined in the demographics file, that nodes must have to be targeted by the intervention. See NodeProperties and IndividualProperties parameters for more information. You can specify AND and OR combinations of key:value pairs with this parameter. |
The following example restricts the intervention to nodes that are urban and medium risk or rural and low risk. {
"Node_Property_Restrictions": [
{
"Place": "URBAN",
"Risk": "MED"
},
{
"Place": "RURAL",
"Risk": "LOW"
}
]
}
|
Percentage_Events_To_Count |
array of strings |
NA |
NA |
NA |
When Threshold_Type equals PERCENTAGE_EVENTS then Percentage_Events_To_Count lists the events that will be counted for the denominator which will then be used with the specified event for Trigger_Condition_List counted for the numerator. |
{
"Event_Coordinator_Config": {
"Coordinator_Name": "ACF_Counter",
"Duration": -1,
"Incidence_Counter": {
"Counter_Event_Type": "NODE",
"Counter_Period": 30,
"Counter_Type": "PERIODIC",
"Demographic_Coverage": 1,
"Node_Property_Restrictions": [],
"Property_Restrictions_Within_Node": [],
"Target_Demographic": "Everyone",
"Trigger_Condition_List": [
"Positive_Event_Node"
]
},
"Responder": {
"Action_List": [
{
"Event_To_Broadcast": "Ind_Start_SIA_2",
"Event_Type": "COORDINATOR",
"Threshold": 0.5
}
],
"Percentage_Events_To_Count": [
"Negative_Event_Node",
"Positive_Event_Node"
],
"Responded_Event": "Respond_To_Surveillance",
"Threshold_Type": "PERCENTAGE_EVENTS"
},
"Start_Trigger_Condition_List": [
"Start_ACF"
],
"Stop_Trigger_Condition_List": [],
"class": "SurveillanceEventCoordinator"
},
"Nodeset_Config": {
"class": "NodeSetAll"
},
"Start_Day": 1,
"class": "CampaignEvent"
}
|
Property_Restrictions |
array of JSON objects |
NA |
NA |
NA |
A list of the IndividualProperty key:value pairs, as defined in the demographics file, that individuals must have to be targeted by this intervention. See NodeProperties and IndividualProperties parameters for more information. To specify AND and OR combinations of key:value pairs, use Property_Restrictions_Within_Node. You cannot use both of these parameters in the same event coordinator. |
{
"Property_Restrictions": [
"Risk:HIGH"
]
}
|
Property_Restrictions_Within_Node |
array of JSON objects |
NA |
NA |
NA |
A list of the IndividualProperty key:value pairs, as defined in the demographics file, that individuals must have to be targeted by this intervention. See NodeProperties and IndividualProperties parameters for more information. This parameter allows you to specify AND and OR combinations of key:value pairs. You may specify individual property restrictions using either this parameter or Property_Restrictions, but not both. |
The following example restricts the intervention to individuals who are urban and high risk or urban and medium risk. {
"Property_Restrictions_Within_Node": [
{
"Geographic": "URBAN",
"Risk": "HIGH"
},
{
"Geographic": "URBAN",
"Risk": "MEDIUM"
}
]
}
|
Responded_Event |
string |
NA |
NA |
“” |
A coordinator event, defined in Custom_Coordinator_Events, that is broadcast if Responder responded. More specifically, at the completion of a counting period, if an action is selected, the action events are broadcast and then the Responded_Event is also broadcast. This allows other event coordinators to react to the action events being broadcast. |
{
"Event_Coordinator_Config": {
"Coordinator_Name": "ACF_Counter",
"Duration": 30,
"Incidence_Counter": {
"Counter_Event_Type": "NODE",
"Counter_Period": 14,
"Counter_Type": "PERIODIC",
"Demographic_Coverage": 1,
"Target_Demographic": "Everyone",
"Trigger_Condition_List": [
"Node_Event_1",
"Node_Event_2"
]
},
"Responder": {
"Action_List": [
{
"Event_To_Broadcast": "Ind_Start_SIA_2",
"Event_Type": "COORDINATOR",
"Threshold": 5
},
{
"Event_To_Broadcast": "Ind_Start_SIA_4",
"Event_Type": "COORDINATOR",
"Threshold": 2
}
],
"Responded_Event": "Respond_To_Surveillance",
"Threshold_Type": "COUNT"
},
"Start_Trigger_Condition_List": [
"Start_ACF"
],
"Stop_Trigger_Condition_List": [
"Start_SIA_2",
"Start_SIA_4"
],
"class": "SurveillanceEventCoordinator"
},
"Nodeset_Config": {
"class": "NodeSetAll"
},
"Start_Day": 1,
"class": "CampaignEvent"
}
|
Responder |
array of JSON objects |
NA |
NA |
NA |
List of JSON objects for specifying the threshold type, values, and the actions to take when the specified conditions and parameters have been met, as configured in Incidence_Counter. Some of the values are specified in the following parameters:
|
{
"Event_Coordinator_Config": {
"Coordinator_Name": "ACF_Counter",
"Duration": 30,
"Incidence_Counter": {
"Counter_Event_Type": "NODE",
"Counter_Period": 14,
"Counter_Type": "PERIODIC",
"Demographic_Coverage": 1,
"Target_Demographic": "Everyone",
"Trigger_Condition_List": [
"Node_Event_1",
"Node_Event_2"
]
},
"Responder": {
"Action_List": [
{
"Event_To_Broadcast": "Ind_Start_SIA_2",
"Event_Type": "COORDINATOR",
"Threshold": 5
},
{
"Event_To_Broadcast": "Ind_Start_SIA_4",
"Event_Type": "COORDINATOR",
"Threshold": 2
}
],
"Responded_Event": "Respond_To_Surveillance",
"Threshold_Type": "COUNT"
},
"Start_Trigger_Condition_List": [
"Start_ACF"
],
"Stop_Trigger_Condition_List": [
"Start_SIA_2",
"Start_SIA_4"
],
"class": "SurveillanceEventCoordinator"
},
"Nodeset_Config": {
"class": "NodeSetAll"
},
"Start_Day": 1,
"class": "CampaignEvent"
}
|
Start_Trigger_Condition_List |
array of strings |
NA |
NA |
NA |
The trigger event list, as specified in the Custom_Coordinator_Events config parameter, that will start Incidence_Counter counting events. The surveillance event coordinator will keep counting and responding until it gets a stop event, as defined in Stop_Trigger_Condition_List, or the duration of the surveillance event coordinator has expired, as defined in Duration. The list cannot be empty. |
{
"class": "CampaignEvent",
"Start_Day": 1,
"Nodeset_Config": {
"class": "NodeSetAll"
},
"Event_Coordinator_Config": {
"class": "SurveillanceEventCoordinator",
"Coordinator_Name": "ACF_Counter",
"Start_Trigger_Condition_List": [
"Start_ACF"
],
"Stop_Trigger_Condition_List": [
"Start_SIA_2",
"Start_SIA_4"
],
"Duration": 30,
"Incidence_Counter": {
"Counter_Type": "PERIODIC",
"Counter_Period": 14,
"Counter_Event_Type": "NODE",
"Trigger_Condition_List": [
"Node_Event_1",
"Node_Event_2"
],
"Target_Demographic": "Everyone",
"Demographic_Coverage": 1
},
"Responder": {
"Responded_Event": "Respond_To_Surveillance",
"Threshold_Type": "COUNT",
"Action_List": [
{
"Threshold": 5,
"Event_Type": "COORDINATOR",
"Event_To_Broadcast": "Ind_Start_SIA_2"
},
{
"Threshold": 2,
"Event_Type": "COORDINATOR",
"Event_To_Broadcast": "Ind_Start_SIA_4"
}
]
}
}
}
|
Stop_Trigger_Condition_List |
array of strings |
NA |
NA |
NA |
The broadcast event list, as specified in the Custom_Coordinator_Events config parameter, that will stop Incidence_Counter counting events. The coordinator can start counting again if it receives a start trigger event. The list can be empty. |
{
"Event_Coordinator_Config": {
"Coordinator_Name": "ACF_Counter",
"Duration": 30,
"Incidence_Counter": {
"Counter_Event_Type": "NODE",
"Counter_Period": 14,
"Counter_Type": "PERIODIC",
"Demographic_Coverage": 1,
"Target_Demographic": "Everyone",
"Trigger_Condition_List": [
"Node_Event_1",
"Node_Event_2"
]
},
"Responder": {
"Action_List": [
{
"Event_To_Broadcast": "Ind_Start_SIA_2",
"Event_Type": "COORDINATOR",
"Threshold": 5
},
{
"Event_To_Broadcast": "Ind_Start_SIA_4",
"Event_Type": "COORDINATOR",
"Threshold": 2
}
],
"Responded_Event": "Respond_To_Surveillance",
"Threshold_Type": "COUNT"
},
"Start_Trigger_Condition_List": [
"Start_ACF"
],
"Stop_Trigger_Condition_List": [
"Start_SIA_2",
"Start_SIA_4"
],
"class": "SurveillanceEventCoordinator"
},
"Nodeset_Config": {
"class": "NodeSetAll"
},
"Start_Day": 1,
"class": "CampaignEvent"
}
|
Target_Age_Max |
float |
0 |
9.3228e+35 |
9.3228e+35 |
The upper end of ages targeted for an intervention, in years. Used when Target_Demographic is set to ExplicitAgeRanges or ExplicitAgeRangesAndGender. |
{
"Target_Age_Max": 20,
"Target_Age_Min": 10,
"Target_Demographic": "ExplicitAgeRanges"
}
|
Target_Age_Min |
float |
0 |
3.40282e+38 |
0 |
The lower end of ages targeted for an intervention, in years. Used when Target_Demographic is set to ExplicitAgeRanges or ExplicitAgeRangesAndGender. |
{
"Target_Age_Max": 20,
"Target_Age_Min": 10,
"Target_Demographic": "ExplicitAgeRanges"
}
|
Target_Demographic |
enum |
NA |
NA |
Everyone |
The target demographic group. Possible values are:
|
{
"Target_Age_Max": 20,
"Target_Age_Min": 10,
"Target_Demographic": "ExplicitAgeRanges"
}
|
Target_Gender |
enum |
NA |
NA |
All |
Specifies the gender restriction for the intervention. Possible values are:
|
{
"Target_Gender": "Female"
}
|
Target_Residents_Only |
boolean |
0 |
1 |
0 |
When set to true (1), only individuals that currently reside in their ‘home’ node will be counted. |
{
"Target_Residents_Only": 1
}
|
Threshold |
float |
0 |
3.40E+3 |
0 |
The COUNT or PERCENTAGE, as configured with Threshold_Type, threshold value that must be met before and action from Action_List will be considered. |
{
"Event_Coordinator_Config": {
"Coordinator_Name": "ACF_Counter",
"Duration": 30,
"Incidence_Counter": {
"Counter_Event_Type": "NODE",
"Counter_Period": 14,
"Counter_Type": "PERIODIC",
"Demographic_Coverage": 1,
"Target_Demographic": "Everyone",
"Trigger_Condition_List": [
"Node_Event_1",
"Node_Event_2"
]
},
"Responder": {
"Action_List": [
{
"Event_To_Broadcast": "Ind_Start_SIA_2",
"Event_Type": "COORDINATOR",
"Threshold": 5
},
{
"Event_To_Broadcast": "Ind_Start_SIA_4",
"Event_Type": "COORDINATOR",
"Threshold": 2
}
],
"Responded_Event": "Respond_To_Surveillance",
"Threshold_Type": "COUNT"
},
"Start_Trigger_Condition_List": [
"Start_ACF"
],
"Stop_Trigger_Condition_List": [
"Start_SIA_2",
"Start_SIA_4"
],
"class": "SurveillanceEventCoordinator"
},
"Nodeset_Config": {
"class": "NodeSetAll"
},
"Start_Day": 1,
"class": "CampaignEvent"
}
|
Threshold_Type |
enum |
NA |
NA |
COUNT |
Threshold type to indicate how Responder handles the count of events from Incidence_Counter and the thresholds in Action_List. Possible values are:
|
{
"Event_Coordinator_Config": {
"Coordinator_Name": "ACF_Counter",
"Duration": 30,
"Incidence_Counter": {
"Counter_Event_Type": "NODE",
"Counter_Period": 14,
"Counter_Type": "PERIODIC",
"Demographic_Coverage": 1,
"Target_Demographic": "Everyone",
"Trigger_Condition_List": [
"Node_Event_1",
"Node_Event_2"
]
},
"Responder": {
"Action_List": [
{
"Event_To_Broadcast": "Ind_Start_SIA_2",
"Event_Type": "COORDINATOR",
"Threshold": 5
},
{
"Event_To_Broadcast": "Ind_Start_SIA_4",
"Event_Type": "COORDINATOR",
"Threshold": 2
}
],
"Responded_Event": "Respond_To_Surveillance",
"Threshold_Type": "COUNT"
},
"Start_Trigger_Condition_List": [
"Start_ACF"
],
"Stop_Trigger_Condition_List": [
"Start_SIA_2",
"Start_SIA_4"
],
"class": "SurveillanceEventCoordinator"
},
"Nodeset_Config": {
"class": "NodeSetAll"
},
"Start_Day": 1,
"class": "CampaignEvent"
}
|
Trigger_Condition_List |
array of strings |
NA |
NA |
NA |
The list of events to count.The list cannot be empty. The type of events contained in the list is determined by Counter_Event_Type. Depending upon the type, the events must be defined in one of the following configuration parameters:
|
{
"Event_Coordinator_Config": {
"Coordinator_Name": "ACF_Counter",
"Duration": 30,
"Incidence_Counter": {
"Counter_Event_Type": "NODE",
"Counter_Period": 14,
"Counter_Type": "PERIODIC",
"Demographic_Coverage": 1,
"Target_Demographic": "Everyone",
"Trigger_Condition_List": [
"Node_Event_1",
"Node_Event_2"
]
},
"Responder": {
"Action_List": [
{
"Event_To_Broadcast": "Ind_Start_SIA_2",
"Event_Type": "COORDINATOR",
"Threshold": 5
},
{
"Event_To_Broadcast": "Ind_Start_SIA_4",
"Event_Type": "COORDINATOR",
"Threshold": 2
}
],
"Responded_Event": "Respond_To_Surveillance",
"Threshold_Type": "COUNT"
},
"Start_Trigger_Condition_List": [
"Start_ACF"
],
"Stop_Trigger_Condition_List": [
"Start_SIA_2",
"Start_SIA_4"
],
"class": "SurveillanceEventCoordinator"
},
"Nodeset_Config": {
"class": "NodeSetAll"
},
"Start_Day": 1,
"class": "CampaignEvent"
}
|
TriggeredEventCoordinator (generic)¶
The TriggeredEventCoordinator coordinator class listens for trigger events, begins a series of repetitions of intervention distributions, and then broadcasts an event upon completion. This campaign event is typically used with other classes that broadcast and distribute events, such as BroadcastCoordinatorEvent, DelayEventCoordinator, and SurveillanceEventCoordinator.
Parameter |
Data type |
Minimum |
Maximum |
Default |
Description |
Example |
|---|---|---|---|---|---|---|
Completion_Event |
array of strings |
NA |
NA |
NA |
The completion event list that will be broadcast every time the triggered event coordinator completes a set of repetitions. The events contained in the list are defined in Custom_Coordinator_Events in the simulation configuration file. |
{
"Event_Coordinator_Config": {
"class": "TriggeredEventCoordinator",
"Coordinator_Name": "1n2_Vaccinator",
"Start_Trigger_Condition_List": [
"Start_Vaccinating_1n2"
],
"Stop_Trigger_Condition_List": [],
"Number_Repetitions": 1,
"Timesteps_Between_Repetitions": 1,
"Duration": -1,
"Target_Demographic": "Everyone",
"Demographic_Coverage": 0.05,
"Intervention_Config": {
"class": "SimpleVaccine",
"Cost_To_Consumer": 1,
"Vaccine_Take": 1,
"Vaccine_Type": "AcquisitionBlocking",
"Waning_Config": {
"class": "WaningEffectBox",
"Initial_Effect": 0.59,
"Box_Duration": 730
}
},
"Completion_Event": "Done_Vaccinating_1n2"
}
}
|
Coordinator_Name |
string |
NA |
NA |
TriggeredEventCoordinator |
The unique identifying coordinator name used to identify the different coordinators in reports. |
{
"Event_Coordinator_Config": {
"Completion_Event": "Done_Vaccinating_1n2",
"Coordinator_Name": "1n2_Vaccinator",
"Demographic_Coverage": 0.05,
"Duration": -1,
"Intervention_Config": {
"Cost_To_Consumer": 1,
"Vaccine_Take": 1,
"Vaccine_Type": "AcquisitionBlocking",
"Waning_Config": {
"Box_Duration": 730,
"Initial_Effect": 0.59,
"class": "WaningEffectBox"
},
"class": "SimpleVaccine"
},
"Number_Repetitions": 1,
"Start_Trigger_Condition_List": [
"Start_Vaccinating_1n2"
],
"Stop_Trigger_Condition_List": [],
"Target_Demographic": "Everyone",
"Timesteps_Between_Repetitions": 1,
"class": "TriggeredEventCoordinator"
}
}
|
Duration |
float |
-1 |
3.40282e+38 |
-1 |
The time period (in days) that the triggered event coordinator is active before it expires. Once the specified duration has been reached the coordinator will expire whether or not it is in the middle of a set of repetitions. The value of -1 (default) equals to never expire. |
{
"Event_Coordinator_Config": {
"Completion_Event": "Done_Vaccinating_1n2",
"Coordinator_Name": "1n2_Vaccinator",
"Demographic_Coverage": 0.05,
"Duration": -1,
"Intervention_Config": {
"Cost_To_Consumer": 1,
"Vaccine_Take": 1,
"Vaccine_Type": "AcquisitionBlocking",
"Waning_Config": {
"Box_Duration": 730,
"Initial_Effect": 0.59,
"class": "WaningEffectBox"
},
"class": "SimpleVaccine"
},
"Number_Repetitions": 1,
"Start_Trigger_Condition_List": [
"Start_Vaccinating_1n2"
],
"Stop_Trigger_Condition_List": [],
"Target_Demographic": "Everyone",
"Timesteps_Between_Repetitions": 1,
"class": "TriggeredEventCoordinator"
}
}
|
Intervention_Config |
JSON object |
NA |
NA |
NA |
The nested JSON of the intervention to be distributed by this event coordinator. |
{
"Event_Coordinator_Config": {
"Completion_Event": "Done_Vaccinating_1n2",
"Coordinator_Name": "1n2_Vaccinator",
"Demographic_Coverage": 0.05,
"Duration": -1,
"Intervention_Config": {
"Cost_To_Consumer": 1,
"Vaccine_Take": 1,
"Vaccine_Type": "AcquisitionBlocking",
"Waning_Config": {
"Box_Duration": 730,
"Initial_Effect": 0.59,
"class": "WaningEffectBox"
},
"class": "SimpleVaccine"
},
"Number_Repetitions": 1,
"Start_Trigger_Condition_List": [
"Start_Vaccinating_1n2"
],
"Stop_Trigger_Condition_List": [],
"Target_Demographic": "Everyone",
"Timesteps_Between_Repetitions": 1,
"class": "TriggeredEventCoordinator"
}
}
|
Node_Property_Restrictions |
array of JSON objects |
NA |
NA |
NA |
A list of the NodeProperty key:value pairs, as defined in the demographics file, that nodes must have to be targeted by the intervention. See NodeProperties and IndividualProperties parameters for more information. You can specify AND and OR combinations of key:value pairs with this parameter. |
The following configuration restrictions the intervention to nodes that are urban and high risk or have had the first round treatment and are low risk. {
"Event_Coordinator_Config": {
"Completion_Event": "Done_Vaccinating_3n4",
"Coordinator_Name": "3n4_Vaccinator",
"Demographic_Coverage": 0.05,
"Duration": -1,
"Intervention_Config": {
"Cost_To_Consumer": 2,
"Vaccine_Take": 1,
"Vaccine_Type": "AcquisitionBlocking",
"Waning_Config": {
"Box_Duration": 730,
"Initial_Effect": 0.59,
"class": "WaningEffectBox"
},
"class": "SimpleVaccine"
},
"Node_Property_Restrictions": [
{
"Place": "Urban",
"Risk": "High"
},
{
"InterventionStatus": "FirstRound",
"Risk": "Low"
}
],
"Number_Repetitions": 3,
"Property_Restrictions_Within_Node": [],
"Start_Trigger_Condition_List": [
"Start_Vaccinating_3n4"
],
"Stop_Trigger_Condition_List": [
"Stop_Vaccinating_3n4"
],
"Target_Demographic": "Everyone",
"Timesteps_Between_Repetitions": 10,
"class": "TriggeredEventCoordinator"
}
}
|
Number_Repetitions |
integer |
-1 |
1000 |
1 |
The number of times an intervention is given, used with Timesteps_Between_Repetitions. |
{
"Event_Coordinator_Config": {
"Completion_Event": "Done_Vaccinating_3n4",
"Coordinator_Name": "3n4_Vaccinator",
"Demographic_Coverage": 0.05,
"Duration": -1,
"Intervention_Config": {
"Cost_To_Consumer": 2,
"Vaccine_Take": 1,
"Vaccine_Type": "AcquisitionBlocking",
"Waning_Config": {
"Box_Duration": 730,
"Initial_Effect": 0.59,
"class": "WaningEffectBox"
},
"class": "SimpleVaccine"
},
"Number_Repetitions": 3,
"Start_Trigger_Condition_List": [
"Start_Vaccinating_3n4"
],
"Stop_Trigger_Condition_List": [
"Stop_Vaccinating_3n4"
],
"Target_Demographic": "Everyone",
"Timesteps_Between_Repetitions": 10,
"class": "TriggeredEventCoordinator"
}
}
|
Property_Restrictions |
array of JSON objects |
NA |
NA |
NA |
A list of the IndividualProperty key:value pairs, as defined in the demographics file, that individuals must have to be targeted by this intervention. See NodeProperties and IndividualProperties parameters for more information. To specify AND and OR combinations of key:value pairs, use Property_Restrictions_Within_Node. You cannot use both of these parameters in the same event coordinator. |
{
"Property_Restrictions": [
"Risk:HIGH"
]
}
|
Property_Restrictions_Within_Node |
array of JSON objects |
NA |
NA |
NA |
A list of the IndividualProperty key:value pairs, as defined in the demographics file, that individuals must have to be targeted by this intervention. See NodeProperties and IndividualProperties parameters for more information. This parameter allows you to specify AND and OR combinations of key:value pairs. You may specify individual property restrictions using either this parameter or Property_Restrictions, but not both. |
The following example restricts the intervention to individuals who are urban and high risk or urban and medium risk. {
"Property_Restrictions_Within_Node": [
{
"Geographic": "URBAN",
"Risk": "HIGH"
},
{
"Geographic": "URBAN",
"Risk": "MEDIUM"
}
]
}
|
Start_Trigger_Condition_List |
array of strings |
NA |
NA |
NA |
The trigger condition event list that when heard will start a new set of repetitions for the triggered event coordinator. The list cannot be empty. The events contained in the list are defined in Custom_Coordinator_Events in the simulation configuration file. |
{
"Event_Coordinator_Config": {
"Completion_Event": "Done_Vaccinating_1n2",
"Coordinator_Name": "1n2_Vaccinator",
"Demographic_Coverage": 0.05,
"Duration": -1,
"Intervention_Config": {
"Cost_To_Consumer": 1,
"Vaccine_Take": 1,
"Vaccine_Type": "AcquisitionBlocking",
"Waning_Config": {
"Box_Duration": 730,
"Initial_Effect": 0.59,
"class": "WaningEffectBox"
},
"class": "SimpleVaccine"
},
"Number_Repetitions": 1,
"Start_Trigger_Condition_List": [
"Start_Vaccinating_1n2"
],
"Stop_Trigger_Condition_List": [],
"Target_Demographic": "Everyone",
"Timesteps_Between_Repetitions": 1,
"class": "TriggeredEventCoordinator"
}
}
|
Stop_Trigger_Condition_List |
array of strings |
NA |
NA |
NA |
The trigger condition event list that when heard will stop any repetitions for the triggered event coordinator until a start trigger condition event list is received. The list can be empty. The events contained in the list are defined in Custom_Coordinator_Events in the simulation configuration file. |
{
"Event_Coordinator_Config": {
"Completion_Event": "Done_Vaccinating_1n2",
"Coordinator_Name": "1n2_Vaccinator",
"Demographic_Coverage": 0.05,
"Duration": -1,
"Intervention_Config": {
"Cost_To_Consumer": 1,
"Vaccine_Take": 1,
"Vaccine_Type": "AcquisitionBlocking",
"Waning_Config": {
"Box_Duration": 730,
"Initial_Effect": 0.59,
"class": "WaningEffectBox"
},
"class": "SimpleVaccine"
},
"Number_Repetitions": 1,
"Start_Trigger_Condition_List": [
"Start_Vaccinating_1n2"
],
"Stop_Trigger_Condition_List": [],
"Target_Demographic": "Everyone",
"Timesteps_Between_Repetitions": 1,
"class": "TriggeredEventCoordinator"
}
}
|
Target_Age_Max |
float |
0 |
9.3228e+35 |
9.3228e+35 |
The upper end of ages targeted for an intervention, in years. Used when Target_Demographic is set to ExplicitAgeRanges or ExplicitAgeRangesAndGender. |
{
"Target_Age_Max": 20,
"Target_Age_Min": 10,
"Target_Demographic": "ExplicitAgeRanges"
}
|
Target_Age_Min |
float |
0 |
3.40E+38 |
0 |
The lower end of ages targeted for an intervention, in years. Used when Target_Demographic is set to ExplicitAgeRanges or ExplicitAgeRangesAndGender. |
{
"Target_Age_Max": 20,
"Target_Age_Min": 10,
"Target_Demographic": "ExplicitAgeRanges"
}
|
Target_Demographic |
enum |
NA |
NA |
Everyone |
The target demographic group. Possible values are:
|
{
"Target_Age_Max": 20,
"Target_Age_Min": 10,
"Target_Demographic": "ExplicitAgeRanges"
}
|
Target_Gender |
enum |
NA |
NA |
All |
Specifies the gender restriction for the intervention. Possible values are:
|
{
"Target_Gender": "Female"
}
|
Target_Residents_Only |
boolean |
0 |
1 |
0 |
When set to true (1), the intervention is only distributed to individuals that began the simulation in the node (i.e. those that claim the node as their residence). |
{
"Target_Residents_Only": 1
}
|
Timesteps_Between_Repetitions |
integer |
-1 |
10000 |
-1 |
The repetition interval. |
{
"Event_Coordinator_Config": {
"Completion_Event": "Done_Vaccinating_1n2",
"Coordinator_Name": "1n2_Vaccinator",
"Demographic_Coverage": 0.05,
"Duration": -1,
"Intervention_Config": {
"Cost_To_Consumer": 1,
"Vaccine_Take": 1,
"Vaccine_Type": "AcquisitionBlocking",
"Waning_Config": {
"Box_Duration": 730,
"Initial_Effect": 0.59,
"class": "WaningEffectBox"
},
"class": "SimpleVaccine"
},
"Number_Repetitions": 1,
"Start_Trigger_Condition_List": [
"Start_Vaccinating_1n2"
],
"Stop_Trigger_Condition_List": [],
"Target_Demographic": "Everyone",
"Timesteps_Between_Repetitions": 1,
"class": "TriggeredEventCoordinator"
}
}
|
Deprecated configuration parameters¶
Base_Population_Scale_Factor has been renamed to x_Base_Population, which is grouped together with the other scale factor parameters beginning with x_. The functional remains the same. Enable_Demographics_Gender has been deprecated. Animal_Reservoir_Type has been replaced with Enable_Infectivity_Reservoir.
The following configuration parameters have been deprecated as a result of the refactoring of distribution parameters for better consistency across the configuration and campaign files.
Parameter |
|---|
Incubation_Period_Log_Mean |
Incubation_Period_Log_Width |
Infectious_Period_Mean |
Infectious_Period_Std_Dev |
Deprecated campaign parameters¶
The following campaign parameters have been deprecated as a result of the refactoring of distribution parameters for better consistency across the configuration and campaign files.
Parameter |
|---|
BitingRisk Constant |
BitingRisk Risk_Distribution_Type |
BitingRisk Exponential_Mean |
BitingRisk Gaussian_Mean |
BitingRisk Gaussian_Std_Dev |
BitingRisk Uniform_Max |
BitingRisk Uniform_Min |
CommunityHealthWorkerEventCoordinator Initial_Amount |
CommunityHealthWorkerEventCoordinator Initial_Amount_Distribution_Type |
CommunityHealthWorkerEventCoordinator Initial_Amount_Mean |
CommunityHealthWorkerEventCoordinator Initial_Amount_Std_Dev |
DelayedIntervention Delay_Distribution |
DelayedIntervention Delay_Period |
DelayedIntervention Delay_Period_Mean |
DelayedIntervention Delay_Period_Scale |
DelayedIntervention Delay_Period_Shape |
DelayedIntervention Delay_Period_Std_Dev |
DelayEventCoordinator Delay_Distribution |
DelayEventCoordinator Delay_Period |
DelayEventCoordinator Delay_Period_Mean |
DelayEventCoordinator Delay_Period_StdDev |
HIVDelayedIntervention Delay_Distribution |
HIVDelayedIntervention Delay_Period |
HIVDelayedIntervention Delay_Period_Mean |
HIVDelayedIntervention Delay_Period_Scale |
HIVDelayedIntervention Delay_Period_Shape |
HIVDelayedIntervention Delay_Period_Std_Dev |
HIVMuxer Delay_Distribution |
HIVMuxer Delay_Period |
HIVMuxer Delay_Period_Mean |
HIVMuxer Delay_Period_Scale |
HIVMuxer Delay_Period_Shape |
HIVMuxer Delay_Period_Std_Dev |
MigrateFamily Duration_At_Node_Distribution_Type |
MigrateFamily Duration_At_Node_Exponential_Period |
MigrateFamily Duration_At_Node_Fixed |
MigrateFamily Duration_At_Node_Gausian_Mean |
MigrateFamily Duration_At_Node_Gausian_StdDev |
MigrateFamily Duration_At_Node_Uniform_Max |
MigrateFamily Duration_At_Node_Uniform_Min |
MigrateFamily Duration_Before_Leaving_Distribution_Type |
MigrateFamily Duration_Before_Leaving_Exponential_Period |
MigrateFamily Duration_Before_Leaving_Fixed |
MigrateFamily Duration_Before_Leaving_Gausian_Mean |
MigrateFamily Duration_Before_Leaving_Gausian_StdDev |
MigrateFamily Duration_Before_Leaving_Uniform_Max |
MigrateFamily Duration_Before_Leaving_Uniform_Min |
MigrateIndividuals Duration_At_Node_Distribution_Type |
MigrateIndividuals Duration_At_Node_Exponential_Period |
MigrateIndividuals Duration_At_Node_Fixed |
MigrateIndividuals Duration_At_Node_Gausian_Mean |
MigrateIndividuals Duration_At_Node_Gausian_StdDev |
MigrateIndividuals Duration_Before_Leaving_Distribution_Type |
MigrateIndividuals Duration_Before_Leaving_Exponential_Period |
MigrateIndividuals Duration_Before_Leaving_Fixed |
MigrateIndividuals Duration_Before_Leaving_Gausian_Mean |
MigrateIndividuals Duration_Before_Leaving_Gausian_StdDev |
MigrateIndividuals Duration_Before_Leaving_Uniform_Max |
MigrateIndividuals Duration_Before_Leaving_Uniform_Min |
MigrateIndividuals Duration_At_Node_Uniform_Max |
MigrateIndividuals Duration_At_Node_Uniform_Min |
UsageDependentBednet Expiration_Distribution_Type |
UsageDependentBednet Expiration_Percentage_Period_1 |
UsageDependentBednet Expiration_Period |
UsageDependentBednet Expiration_Period_1 |
UsageDependentBednet Expiration_Period_2 |
UsageDependentBednet Expiration_Period_Mean |
UsageDependentBednet Expiration_Period_Std_Dev |
EMOD v2.18¶
The EMOD v2.18 release includes many new features for all supported simulation types. In particular, the TB_SIM simulation type has been deprecated and replaced with TBHIV_SIM, which does not include HIV transmission but adds the ability to model the effect of HIV coinfection on the spread of TB.
New configuration parameters¶
For the malaria simulation type, the following new configuration parameters are available:
Parameter |
Data type |
Minimum |
Maximum |
Default |
Description |
Example |
|---|---|---|---|---|---|---|
Genome_Markers |
array of strings |
NA |
NA |
NA |
A list of the names (strings) of genome marker(s) that represent the genetic components in a strain of an infection. |
{
"Genome_Markers": [
"D6",
"W2"
]
}
|
Resistance |
JSON object |
NA |
NA |
NA |
Specifies the drug resistance multiplier. |
{
"parameters": {
"Genome_Markers": [
"A",
"B"
],
"Malaria_Drug_Params": {
"Artemether_Lumefantrine": {
"Bodyweight_Exponent": 0,
"Drug_Cmax": 1000,
"Drug_Decay_T1": 1,
"Drug_Decay_T2": 1,
"Drug_Dose_Interval": 1,
"Drug_Fulltreatment_Doses": 3,
"Drug_Gametocyte02_Killrate": 2.3,
"Drug_Gametocyte34_Killrate": 2.3,
"Drug_GametocyteM_Killrate": 0,
"Drug_Hepatocyte_Killrate": 0,
"Drug_PKPD_C50": 100,
"Drug_Vd": 10,
"Max_Drug_IRBC_Kill": 3.45
"Resistance": {
"A": {
"Max_IRBC_Kill_Modifier": 0.05,
"PKPD_C50_Modifier": 1.0
},
"B": {
"Max_IRBC_Kill_Modifier": 0.25,
"PKPD_C50_Modifier": 1.0
}
}
}
}
}
}
|
To view all available configuration parameters, see Configuration parameters.
New campaign parameters¶
The following campaign classes are new for the Generic model and can be used in all other models:
IncidenceEventCoordinator (generic)¶
The IncidenceEventCoordinator coordinator class distributes interventions based on the number of events counted over a period of time.
Parameter |
Data type |
Minimum |
Maximum |
Default |
Description |
Example |
|---|---|---|---|---|---|---|
Action_List |
array of JSON objects |
NA |
NA |
NA |
List (array) of JSON objects, including the values specified in the following parameters: Threshold, Event_To_Broadcast. |
{
"Threshold_Type": "COUNT",
"Action_List": [
{
"Threshold": 20,
"Event_To_Broadcast": "Action_Event_1"
},
{
"Threshold": 30,
"Event_To_Broadcast": "Action_Event_2"
}
]
}
|
Count_Events_For_Num_Timesteps |
integer |
1 |
2.15E+00 |
1 |
If set to true (1), then the waning effect values, as specified in the Effect_List list of objects for the WaningEffectCombo classes, are added together. If set to false (0), the waning effect values are multiplied. The resulting waning effect value cannot be greater than 1. |
{
"Incidence_Counter": {
"Count_Events_For_Num_Timesteps": 5,
"Trigger_Condition_List": [
"PropertyChange"
],
"Node_Property_Restrictions": [
{
"Risk": "HIGH"
}
],
"Target_Demographic": "Everyone",
"Demographic_Coverage": 0.6,
"Property_Restrictions_Within_Node": [
{
"Accessibility": "YES"
}
]
}
}
|
Event_To_Broadcast |
string |
NA |
NA |
NA |
The action event to occur when the specified trigger value in the Threshold parameter is met. At least one action must be defined for Event_To_Broadcast. The events contained in the list can be built-in events (see Event list for possible events). |
{
"Threshold_Type": "COUNT",
"Action_List": [
{
"Threshold": 20,
"Event_To_Broadcast": "Action_Event_1"
},
{
"Threshold": 30,
"Event_To_Broadcast": "Action_Event_2"
}
]
}
|
Incidence_Counter |
array of JSON objects |
NA |
NA |
NA |
List of JSON objects for specifying the conditions and parameters that must be met for an incidence to be counted. Some of the values are specified in the following parameters: Count_Events_For_Num_Timesteps, Trigger_Condition_List, Node_Property_Restrictions. |
{
"Incidence_Counter": {
"Count_Events_For_Num_Timesteps": 5,
"Trigger_Condition_List": [
"PropertyChange"
],
"Node_Property_Restrictions": [
{
"Risk": "HIGH"
}
],
"Target_Demographic": "Everyone",
"Demographic_Coverage": 0.6,
"Property_Restrictions_Within_Node": [
{
"Accessibility": "YES"
}
]
}
}
|
Node_Property_Restrictions |
array of JSON objects |
NA |
NA |
NA |
A list of the NodeProperty key:value pairs, as defined in the demographics file, that nodes must have to be targeted by the intervention. See NodeProperties and IndividualProperties parameters for more information. You can specify AND and OR combinations of key:value pairs with this parameter. |
The following example restricts the intervention to nodes that are urban and medium risk or rural and low risk. {
"Node_Property_Restrictions": [
{
"Place": "URBAN",
"Risk": "MED"
},
{
"Place": "RURAL",
"Risk": "LOW"
}
]
}
|
Number_Repetitions |
integer |
-1 |
1000 |
1 |
The number of times an intervention is given, used with Timesteps_Between_Repetitions. |
{
"class": "IncidenceEventCoordinator",
"Number_Repetitions": 3
}
|
Responder |
array of JSON objects |
NA |
NA |
NA |
List of JSON objects for specifying the threshold type, values, and the actions to take when the specified conditions and parameters have been met, as configured in the Incidence_Counter parameter. Some of the values are specified in the following parameters:
|
{
"Responder": {
"Threshold_Type": "COUNT",
"Action_List": [
{
"Threshold": 5,
"Event_To_Broadcast": "Action_Event_1"
},
{
"Threshold": 10,
"Event_To_Broadcast": "Action_Event_2"
}
]
}
}
|
Threshold |
float |
0 |
3.40E+03 |
0 |
The threshold value that triggers the specified action for the Event_To_Broadcast parameter. When you use the Threshold parameter you must also use the Event_To_Broadcast parameter. |
{
"Threshold_Type": "COUNT",
"Action_List": [
{
"Threshold": 20,
"Event_To_Broadcast": "Action_Event_1"
},
{
"Threshold": 30,
"Event_To_Broadcast": "Action_Event_2"
}
]
}
|
Threshold_Type |
enum |
NA |
NA |
COUNT |
Threshold type. Possible values are:
|
{
"Threshold_Type": "COUNT",
"Action_List": [
{
"Threshold": 20,
"Event_To_Broadcast": "Action_Event_1"
},
{
"Threshold": 30,
"Event_To_Broadcast": "Action_Event_2"
}
]
}
|
Timesteps_Between_Repetitions |
integer |
-1 |
1000 |
-1 |
The repetition interval. |
{
"class": "IncidenceEventCoordinator",
"Number_Repetitions": 3,
"Timesteps_Between_Repetitions": 6
}
|
Trigger_Condition_List |
array of strings |
NA |
NA |
NA |
A list of events that will trigger an intervention. |
{
"Trigger_Condition_List": [
"NewClinicalCase",
"NewSevereCase"
]
}
|
MultiNodeInterventionDistributor (generic)¶
The MultiNodeInterventionDistributor intervention class distributes multiple node-level interventions when the distributor only allows specifying one intervention.
Parameter |
Data type |
Minimum |
Maximum |
Default |
Description |
Example |
|---|---|---|---|---|---|---|
Disqualifying_Properties |
array of strings |
NA |
NA |
[] |
A list of NodeProperty key:value pairs that cause an intervention to be aborted (persistent interventions will stop being distributed to individuals with these values). See NodeProperties and IndividualProperties parameters for more information. Generally used to control the flow of health care access. For example, to prevent the same individual from accessing health care via two different routes at the same time. |
{
"Disqualifying_Properties": [
"InterventionStatus:LostForever"
]
}
|
Intervention_Name |
string |
NA |
NA |
NA |
The optional name used to refer to this intervention as a means to differentiate it from others that use the same class. |
{
"Intervention_Config": {
"class": "MultiNodeInterventionDistributor",
"Intervention_Name": "Country-wide vaccination"
}
}
|
New_Property_Value |
string |
NA |
NA |
NA |
An optional NodeProperty key:value pair that will be assigned when the intervention is distributed. See NodeProperties and IndividualProperties parameters for more information. Generally used to indicate the broad category of health care cascade to which an intervention belongs to prevent individuals from accessing care through multiple pathways. For example, if an individual must already be taking a particular medication to be prescribed a new one. |
{
"New_Property_Value": "InterventionStatus:None"
}
|
Node_Intervention_List |
array of JSON objects |
NA |
NA |
NA |
A list of nested JSON objects for the multi-node-level interventions to be distributed by this intervention. |
{
"Intervention_Config": {
"class": "MultiNodeInterventionDistributor",
"Node_Intervention_List": [
{
"class": "SpaceSpraying",
"Cost_To_Consumer": 1.0,
"Habitat_Target": "ALL_HABITATS",
"Spray_Kill_Target": "SpaceSpray_Indoor",
"Killing_Config": {
"class": "WaningEffectExponential",
"Initial_Effect": 1.0,
"Decay_Time_Constant": 90
},
"Reduction_Config": {
"class": "WaningEffectExponential",
"Initial_Effect": 1.0,
"Decay_Time_Constant": 90
}
},
{
"class": "NodePropertyValueChanger",
"Target_NP_Key_Value": "InterventionStatus:RECENT_SPRAY",
"Daily_Probability": 1.0,
"Maximum_Duration": 0,
"Revert": 90
}
]
}
}
|
WaningEffectCombo (generic)¶
The WaningEffectCombo class is used within individual-level interventions and allows for specifiying a list of effects when the intervention only has one WaningEffect defined. These effects can be added or multiplied.
Parameter |
Data type |
Minimum |
Maximum |
Default |
Description |
Example |
|---|---|---|---|---|---|---|
Add_Effects |
boolean |
0 |
1 |
0 |
The Add_Effects parameter allows you to combine multiple effects from the waning effect classes. If set to true (1), then the waning effect values from the different waning effect objects are added together. If set to false (0), the waning effect values are multiplied. The resulting waning effect value must be greater than 1. |
{
"class": "WaningEffectCombo",
"Add_Effects": 1,
"Expires_When_All_Expire": 0,
"Effect_List": [
{
"class": "WaningEffectMapLinear",
"Initial_Effect": 1.0,
"Expire_At_Durability_Map_End": 1,
"Durability_Map": {
"Times": [
0.0,
1.0,
2.0
],
"Values": [
0.2,
0.4,
0.6
]
}
},
{
"class": "WaningEffectBox",
"Initial_Effect": 0.5,
"Box_Duration": 5.0
}
]
}
|
Effect_List |
array of JSON objects |
NA |
NA |
NA |
A list of nested JSON parameters to indicate how the intervention efficacy wanes over time. |
{
"class": "WaningEffectCombo",
"Add_Effects": 1,
"Expires_When_All_Expire": 0,
"Effect_List": [
{
"class": "WaningEffectMapLinear",
"Initial_Effect": 1.0,
"Expire_At_Durability_Map_End": 1,
"Durability_Map": {
"Times": [
0.0,
1.0,
2.0
],
"Values": [
0.2,
0.4,
0.6
]
}
},
{
"class": "WaningEffectBox",
"Initial_Effect": 0.5,
"Box_Duration": 5.0
}
]
}
|
Expires_When_All_Expire |
boolean |
0 |
1 |
0 |
If set to true (1), then all of the effects, as specified in the Effect_List parameter, must expire for the efficacy of the intervention to expire. If set to false (0), then the efficacy of the intervention will expire as soon as one of the parameters expires. |
{
"class": "WaningEffectCombo",
"Add_Effects": 1,
"Expires_When_All_Expire": 0,
"Effect_List": [
{
"class": "WaningEffectMapLinear",
"Initial_Effect": 1.0,
"Expire_At_Durability_Map_End": 1,
"Durability_Map": {
"Times": [
0.0,
1.0,
2.0
],
"Values": [
0.2,
0.4,
0.6
]
}
},
{
"class": "WaningEffectBox",
"Initial_Effect": 0.5,
"Box_Duration": 5.0
}
]
}
|
The following campaign classes are new for the Malaria model:
AdherentDrug (malaria)¶
The AdherentDrug class extends AntiMalarialDrug class and allows for incorporating different patterns of adherence to taking the drug.
Parameter |
Data type |
Minimum |
Maximum |
Default |
Description |
Example |
|---|---|---|---|---|---|---|
Adherence_Config |
array of JSON objects |
NA |
NA |
NA |
A list of nested JSON objects for the interventions to be distributed by this event coordinator. |
{
"Adherence_Config": {
"class": "WaningEffectMapCount",
"Initial_Effect": 1.0,
"Durability_Map": {
"Times": [
1.0,
2.0,
3.0,
4.0
],
"Values": [
0.1,
0.1,
0.1,
0.1
]
}
}
}
|
Cost_To_Consumer |
float |
0 |
99999 |
1 |
The unit cost per drug (unamortized). |
{
"Cost_To_Consumer": 10
}
|
Disqualifying_Properties |
array of strings |
NA |
NA |
[] |
A list of IndividualProperty key:value pairs that cause an intervention to be aborted (persistent interventions will stop being distributed to nodes with these values). See NodeProperties and IndividualProperties parameters for more information. Generally used to control the flow of health care access. For example, to prevent the same individual from accessing health care via two different routes at the same time. |
{
"Disqualifying_Properties": [
"InterventionStatus:LostForever"
]
}
|
Dont_Allow_Duplicates |
boolean |
0 |
1 |
0 |
If an individual’s container has an intervention, set to true (1) to prevent them from receiving another copy of the intervention. Supported by all intervention classes. |
{
"Dont_Allow_Duplicates": 0
}
|
Dosing_Type |
enum |
NA |
NA |
SingleDose |
The type of anti-malarial dosing to distribute in a drug intervention. Possible values are:
|
{
"Intervention_Config": {
"Cost_To_Consumer": 3.75,
"Dosing_Type": "FullTreatmentWhenSymptom",
"Drug_Type": "Chloroquine",
"class": "AntimalarialDrug"
}
}
|
Intervention_Name |
string |
NA |
NA |
AdherentDrug |
The optional name used to refer to this intervention as a means to differentiate it from others that use the same class. |
{
"Intervention_Config": {
"class": "AdherentDrug",
"Intervention_Name": "Isoniazid with mediocre adherence"
}
}
|
Max_Dose_Consideration_Duration |
float |
1.0/24.0 (1hr) |
3.40E+03 |
3.40E+03 |
The maximum number of days that an individual will consider taking the doses of the drug. |
{
"class": "AdherentDrug",
"Cost_To_Consumer": 1,
"Drug_Type": "TestDrug",
"Dosing_Type": "FullTreatmentCourse",
"Adherence_Config": {
"class": "WaningEffectMapCount",
"Initial_Effect": 1.0,
"Durability_Map": {
"Times": [
1.0,
2.0,
3.0
],
"Values": [
1.0,
0.0,
1.0
]
}
},
"Non_Adherence_Options": [
"NEXT_DOSAGE_TIME"
],
"Non_Adherence_Distribution": [
1.0
],
"Max_Dose_Consideration_Duration": 4,
"Took_Dose_Event": "NewClinicalCase"
}
|
New_Property_Value |
string |
NA |
NA |
NA |
An optional IndividualProperty key:value pair that will be assigned when the intervention is distributed. See NodeProperties and IndividualProperties parameters for more information. Generally used to indicate the broad category of health care cascade to which an intervention belongs to prevent individuals from accessing care through multiple pathways. For example, if an individual must already be taking a particular medication to be prescribed a new one. |
{
"New_Property_Value": "InterventionStatus:None"
}
|
Non_Adherence_Distribution |
array of floats |
0 |
1 |
0 |
The non adherence probability value(s) assigned to the corresponding options in Non_Adherence_Options. The sum of non adherence distribution values must equal a total of 1. |
{
"Non_Adherence_Distribution": [
0.7,
0.3
]
}
|
Non_Adherence_Options |
array of strings |
NA |
NA |
NEXT_UPDATE |
Defines the action the person takes if they do not take a particular dose, are not adherent. |
{
"AD_Non_Adherence_Options": [
"NEXT_DOSAGE_TIME",
"NEXT_UPDATE"
]
}
|
Took_Dose_Event |
string |
NA |
NA |
“” |
The event that triggers the drug intervention campaign. The events contained in the list can be built-in events (see Event list for possible events). |
{
"class": "AdherentDrug",
"Cost_To_Consumer": 1,
"Drug_Type": "TestDrug",
"Dosing_Type": "FullTreatmentCourse",
"Adherence_Config": {
"class": "WaningEffectMapCount",
"Initial_Effect": 1.0,
"Durability_Map": {
"Times": [
1.0,
2.0,
3.0
],
"Values": [
1.0,
0.0,
1.0
]
}
},
"Non_Adherence_Options": [
"NEXT_DOSAGE_TIME"
],
"Non_Adherence_Distribution": [
1.0
],
"Max_Dose_Consideration_Duration": 4,
"Took_Dose_Event": "NewClinicalCase"
}
|
BitingRisk (malaria, vector)¶
The BitingRisk class is used with individual-level interventions and allows for adjusting the relative risk of being bitten by a vector.
Parameter |
Data type |
Minimum |
Maximum |
Default |
Description |
Example |
|---|---|---|---|---|---|---|
Disqualifying_Properties |
array of strings |
NA |
NA |
[] |
A list of IndividualProperty key:value pairs that cause an intervention to be aborted (persistent interventions will stop being distributed to individuals with these values). See NodeProperties and IndividualProperties parameters for more information. Generally used to control the flow of health care access. For example, to prevent the same individual from accessing health care via two different routes at the same time. |
{
"Disqualifying_Properties": [
"InterventionStatus:LostForever"
]
}
|
Dont_Allow_Duplicates |
boolean |
0 |
1 |
0 |
If an individual’s container has an intervention, set to true (1) to prevent them from receiving another copy of the intervention. Supported by all intervention classes. |
{
"Dont_Allow_Duplicates": 0
}
|
Intervention_Name |
string |
NA |
NA |
BitingRisk |
The optional name used to refer to this intervention as a means to differentiate it from others that use the same class. |
{
"Intervention_Config": {
"class": "BitingRisk",
"Intervention_Name": "Relative biting risk with bednet usage"
}
}
|
New_Property_Value |
string |
NA |
NA |
NA |
An optional IndividualProperty key:value pair that will be assigned when the intervention is distributed. See NodeProperties and IndividualProperties parameters for more information. Generally used to indicate the broad category of health care cascade to which an intervention belongs to prevent individuals from accessing care through multiple pathways. For example, if an individual must already be taking a particular medication to be prescribed a new one. |
{
"New_Property_Value": "InterventionStatus:None"
}
|
Risk_Constant |
float |
0 |
3.40282E+38 |
6 |
The risk to use for all individuals when Risk_Distribution is set to CONSTANT_DISTRIBUTION. |
{
"Risk_Distribution": "CONSTANT_DISTRIBUTION",
"Risk_Constant": 8
}
|
Risk_Distribution |
enum |
NA |
NA |
NOT_INITIALIZED |
The distribution type to use for assigning the relative risk of being bitten by a mosquito to each individual. Each assigned value is a random draw from the distribution. Possible values are:
|
{
"Risk_Distribution": "WEIBULL_DISTRIBUTION",
"Risk_Kappa": 0.9,
"Risk_Lambda": 1.5
}
|
Risk_Exponential |
float |
0 |
3.40282E+38 |
6 |
The mean of the biting risk when Risk_Distribution is set to EXPONENTIAL_DISTRIBUTION. |
{
"Risk_Distribution": "EXPONENTIAL_DISTRIBUTION",
"Risk_Exponential": 4.25
}
|
Risk_Gaussian_Mean |
float |
0 |
3.40282E+38 |
6 |
The mean of the biting risk when Risk_Distribution is set to GAUSSIAN_DISTRIBUTION. |
{
"Risk_Distribution": "GAUSSIAN_DISTRIBUTION",
"Risk_Gaussian_Mean": 8,
"Risk_Gaussian_Std_Dev": 1.5
}
|
Risk_Gaussian_Std_Dev |
float |
1.17549E-38 |
3.40282E+38 |
1 |
The standard deviation of the biting risk when Risk_Distribution is set to GAUSSIAN_DISTRIBUTION. |
{
"Risk_Distribution": "GAUSSIAN_DISTRIBUTION",
"Risk_Gaussian_Mean": 8,
"Risk_Gaussian_Std_Dev": 1.5
}
|
Risk_Kappa |
float |
1.17549E-38 |
3.40282E+38 |
1 |
The shape value for the biting risk when Risk_Distribution is set to WEIBULL_DISTRIBUTION. |
{
"Risk_Distribution": "WEIBULL_DISTRIBUTION",
"Risk_Kappa": 0.9,
"Risk_Lambda": 1.5
}
|
Risk_Lambda |
float |
1.17549E-38 |
3.40282E+38 |
1 |
The scale value for the biting risk when Risk_Distribution is set to WEIBULL_DISTRIBUTION. |
{
"Risk_Distribution": "WEIBULL_DISTRIBUTION",
"Risk_Kappa": 0.9,
"Risk_Lambda": 1.5
}
|
Risk_Log_Normal_Mu |
float |
-3.40282e+38 |
3.40282E+38 |
6 |
The mean of the biting risk when Risk_Distribution is set to LOG_NORMAL_DISTRIBUTION. |
{
"Risk_Distribution": "LOG_NORMAL_DISTRIBUTION",
"Risk_Log_Normal_Mu": 9,
"Risk_Log_Normal_Sigma": 2
}
|
Risk_Log_Normal_Sigma |
float |
-3.40282e+38 |
3.40282E+38 |
1 |
The width of the biting risk when Risk_Distribution is set to LOG_NORMAL_DISTRIBUTION. |
{
"Risk_Distribution": "LOG_NORMAL_DISTRIBUTION",
"Risk_Log_Normal_Mu": 9,
"Risk_Log_Normal_Sigma": 2
}
|
Risk_Max |
float |
0 |
3.40282E+38 |
1 |
The maximum biting risk when Risk_Distribution is set to UNIFORM_DISTRIBUTION. |
{
"Risk_Distribution": "UNIFORM_DISTRIBUTION",
"Risk_Min": 2,
"Risk_Max": 7
}
|
Risk_Mean_1 |
float |
1.17549E-38 |
3.40282E+38 |
1 |
The mean of the first exponential distribution when Risk_Distribution is set to DUAL_EXPONENTIAL_DISTRIBUTION. |
{
"Risk_Distribution": "DUAL_EXPONENTIAL_DISTRIBUTION",
"Risk_Mean_1": 4,
"Risk_Mean_2": 12,
"Risk_Proportion_1": 0.2
}
|
Risk_Mean_2 |
float |
1.17549E-38 |
3.40282E+38 |
1 |
The mean of the second exponential distribution when Risk_Distribution is set to DUAL_EXPONENTIAL_DISTRIBUTION. |
{
"Risk_Distribution": "DUAL_EXPONENTIAL_DISTRIBUTION",
"Risk_Mean_1": 4,
"Risk_Mean_2": 12,
"Risk_Proportion_1": 0.2
}
|
Risk_Min |
float |
0 |
3.40282E+38 |
0 |
The minimum biting risk when Risk_Distribution is set to UNIFORM_DISTRIBUTION. |
{
"Risk_Distribution": "UNIFORM_DISTRIBUTION",
"Risk_Min": 2,
"Risk_Max": 7
}
|
Risk_Peak_2_Value |
float |
0 |
3.40282E+38 |
1 |
The biting risk value to assign to the remaining individuals when Risk_Distribution is set to DUAL_CONSTANT_DISTRIBUTION. |
{
"Risk_Distribution": "DUAL_CONSTANT_DISTRIBUTION",
"Risk_Proportion_0": 0.25,
"Risk_Peak_2_Value": 5
}
|
Risk_Poisson_Mean |
float |
0 |
3.40282E+38 |
6 |
The mean of the biting risk when Risk_Distribution is set to POISSON_DISTRIBUTION. |
{
"Risk_Distribution": "POISSON_DISTRIBUTION",
"Risk_Poisson_Mean": 5
}
|
Risk_Proportion_0 |
float |
0 |
1 |
1 |
The proportion of individuals to assign a value of zero biting risk when Risk_Distribution is set to DUAL_CONSTANT_DISTRIBUTION. |
{
"Risk_Distribution": "DUAL_CONSTANT_DISTRIBUTION",
"Risk_Proportion_0": 0.25,
"Risk_Peak_2_Value": 5
}
|
Risk_Proportion_1 |
float |
0 |
1 |
1 |
The proportion of individuals in the first exponential distribution when Risk_Distribution is set to DUAL_EXPONENTIAL_DISTRIBUTION. |
{
"Risk_Distribution": "DUAL_EXPONENTIAL_DISTRIBUTION",
"Risk_Mean_1": 4,
"Risk_Mean_2": 12,
"Risk_Proportion_1": 0.2
}
|
OutbreakIndividualMalaria (malaria)¶
The OutbreakIndividualMalaria class extends OutbreakIndividual class and allows for specifying a specific strain of infection.
Parameter |
Data type |
Minimum |
Maximum |
Default |
Description |
Example |
|---|---|---|---|---|---|---|
Antigen |
integer |
0 |
10 |
0 |
The antigenic base strain ID of the outbreak infection. This must not exceed the number specified in the configuration parameter Number_Basestrains. |
{
"Intervention_Config": {
"Antigen": 0,
"Genome": 0,
"Outbreak_Source": "PrevalenceIncrease",
"class": "OutbreakIndividual"
}
}
|
Create_Random_Genome |
boolean |
0 |
1 |
0 |
If set to true (1), then a random genome is created for the infection and the Genome_Markers parameter is not used. If set to false (0), then you must define the Genome_Markers parameter which allows you to then specify genetic components in a strain of infection. |
{
"OIM_Create_Random_Genome": 1
}
|
Genome_Markers |
array of strings |
NA |
NA |
NA |
A list of the names of genome marker(s) that represent the genetic components in a strain of an infection. |
{
"Intervention_Config": {
"class": "OutbreakIndividualMalaria",
"Antigen": 0,
"Genome_Markers": [
"D6",
"W2"
]
}
}
|
Ignore_Immunity |
boolean |
0 |
1 |
1 |
Individuals will be force-infected (with a specific strain) regardless of actual immunity level when set to true (1). |
{
"Intervention_Config": {
"Antigen": 0,
"Genome": 0,
"class": "OutbreakIndividual",
"Ignore_Immunity": 0
}
}
|
Incubation_Period_Override |
integer |
-1 |
2.15E+0 |
-1 |
The incubation period, in days, that infected individuals will go through before becoming infectious. This value overrides the incubation period set in the configuration file. Set to -1 to honor the configuration parameter settings. |
{
"Incubation_Period_Override": 0
}
|
The following campaign class is new for the TBHIV model:
TBHIVConfigurableTBdrug (tuberculosis)¶
The TBHIVConfigurableTBdrug class is an individual level intervention for TB treatment. The intervention applies TB drug effects to the progression, associated mortality, transmission and acquisition of TB infections in HIV positive and negative individuals.
Parameter |
Data type |
Minimum |
Maximum |
Default |
Description |
Example |
|---|---|---|---|---|---|---|
Active_Multiplier |
array of floats |
0 |
1 |
1 |
Multiplier of clearance/inactivation if active TB on drug treatment. Relapse, mortality, and resistance apply only to active. |
{
"Active_Multiplier": 1
}
|
Cost_To_Consumer |
float |
0 |
99999 |
1 |
The unit cost per drug (unamortized). |
{
"Cost_To_Consumer": 10
}
|
Disqualifying_Properties |
array of strings |
NA |
NA |
[] |
A list of IndividualProperty key:value pairs that cause an intervention to be aborted (persistent interventions will stop being distributed to individuals with these values). See NodeProperties and IndividualProperties parameters for more information. Generally used to control the flow of health care access. For example, to prevent the same individual from accessing health care via two different routes at the same time. |
{
"Disqualifying_Properties": [
"InterventionStatus:LostForever"
]
}
|
Dont_Allow_Duplicates |
boolean |
0 |
1 |
0 |
If an individual’s container has an intervention, set to true (1) to prevent them from receiving another copy of the intervention. Supported by all intervention classes. |
{
"Dont_Allow_Duplicates": 0
}
|
Dose_Interval |
float |
0 |
99999 |
1 |
The interval between doses, in days. |
{
"Dose_Interval": 1
}
|
Drug_Cmax |
float |
0 |
10000 |
1 |
The maximum drug concentration that can be used, and is in the same units as Drug_PKPD_C50. Since drug concentrations and C50 values are often specified with different unit systems, these two parameters have been designed to be flexible provided that the units are the same for each. This parameter is used when Durability_Profile is set to CONCENTRATION_VERSUS_TIME. |
{
"Durability_Profile": "CONCENTRATION_VERSUS_TIME",
"Drug_Cmax": 200,
"Drug_PKPD_C50": 6,
"Drug_Vd": 1
}
|
Drug_PKPD_C50 |
float |
0 |
10000 |
1 |
The concentration at which drug killing rates are half of the maximum. Must use the same units as Drug_Cmax. This parameter is used when Durability_Profile is set to CONCENTRATION_VERSUS_TIME. |
{
"Durability_Profile": "CONCENTRATION_VERSUS_TIME",
"Drug_Cmax": 200,
"Drug_PKPD_C50": 6,
"Drug_Vd": 1
}
|
Drug_Vd |
float |
0 |
10000 |
1 |
The volume of drug distribution. This value is the ratio of the volume of the second compartment to the volume of the first compartment in a two-compartment model, and is dimensionless. This parameter is used when Durability_Profile is set to CONCENTRATION_VERSUS_TIME. |
{
"Durability_Profile": "CONCENTRATION_VERSUS_TIME",
"Drug_Cmax": 200,
"Drug_PKPD_C50": 6,
"Drug_Vd": 1
}
|
Durability_Profile |
enum |
NA |
NA |
FIXED_DURATION_CONSTANT_EFFECT |
The profile of durability decay. Possible values are:
|
{
"Durability_Profile": "CONCENTRATION_VERSUS_TIME",
"Drug_Cmax": 200,
"Drug_PKPD_C50": 6,
"Drug_Vd": 1
}
|
Fraction_Defaulters |
float |
0 |
1 |
0 |
The fraction of individuals who will not finish their drug treatment. |
{
"Fraction_Defaulters": 0
}
|
Intervention_Name |
string |
NA |
NA |
NA |
The optional name used to refer to this intervention as a means to differentiate it from others that use the same class. |
{
"Intervention_Config": {
"class": "TBHIVConfigurableTBdrug",
"Intervention_Name": "Isoniazid distribution"
}
}
|
Latency_Multiplier |
array of floats |
0 |
1 |
1 |
Multiplier of clearance/inactivation if latent TB on drug treatment for the TB drug cure rate parameters (TB_Drug_Cure_Rate, TB_Drug_Cure_Rate_MDR, TB_Drug_Cure_Rate_HIV ) and the TB drug inactivation rate parameters (TB_Drug_Inactivation_Rate, TB_Drug_Inactivation_Rate_MDR, TB_Drug_Inactivation_Rate_HIV). |
{
"Latency_Multiplier": 1
}
|
New_Property_Value |
string |
NA |
NA |
NA |
An optional IndividualProperty key:value pair that will be assigned when the intervention is distributed. See NodeProperties and IndividualProperties parameters for more information. Generally used to indicate the broad category of health care cascade to which an intervention belongs to prevent individuals from accessing care through multiple pathways. For example, if an individual must already be taking a particular medication to be prescribed a new one. |
{
"New_Property_Value": "InterventionStatus:None"
}
|
Primary_Decay_Time_Constant |
float |
0 |
1.00E+00 |
0 |
The primary decay time constant (in days) of the decay profile. |
{
"Primary_Decay_Time_Constant": 180
}
|
Remaining_Doses |
integer |
0 |
999999 |
0 |
The remaining doses in an intervention; enter a negative number for unlimited doses. |
{
"Remaining_Doses": 1
}
|
Secondary_Decay_Time_Constant |
float |
0 |
999999 |
1 |
The secondary decay time constant of the durability profile. This parameter is used when Durability_Profile is set to CONCENTRATION_VERSUS_TIME. |
{
"Durability_Profile": "CONCENTRATION_VERSUS_TIME",
"Secondary_Decay_Time_Constant": 730
}
|
TB_Drug_Name |
string |
NA |
NA |
NA |
The name of TB drug used in the TBHIVConfigurationTBdrug intervention. This must be one of the listed drugs as specificed under TBHIV_Drug_Types in the configuration file. |
{
"Active_Multiplier": 1,
"Durability_Profile": "FIXED_DURATION_CONSTANT_EFFECT",
"Latency_Multiplier": 1,
"Remaining_Doses": 1,
"TB_Drug_Name": "PreDOTSLowNoMDR",
"class": "TBHIVConfigurableTBdrug"
}
|
TB_Reduced_Acquire |
array of floats |
0 |
1 |
0 |
Proportion reduction in acquisition of new TB infection under drug treatment. Only relevant when TB_Enable_Exogenous is enabled to allow exogenous re-infection. |
{
"TBHIV_Drug_Params": {
"ACFDOTS": {
"TB_Drug_Cure_Rate": 0.25,
"TB_Drug_Inactivation_Rate": 1e-09,
"TB_Drug_Inactivation_Rate_HIV": 1e-09,
"TB_Drug_Inactivation_Rate_MDR": 1e-09,
"TB_Drug_Mortality_Rate": 1e-09,
"TB_Drug_Mortality_Rate_HIV": 1e-09,
"TB_Drug_Mortality_Rate_MDR": 1e-09,
"TB_Drug_Primary_Decay_Time_Constant": 179,
"TB_Drug_Relapse_Rate": 1e-09,
"TB_Drug_Relapse_Rate_HIV": 1e-09,
"TB_Drug_Relapse_Rate_MDR": 1e-09,
"TB_Drug_Resistance_Rate": 1e-09,
"TB_Drug_Resistance_Rate_HIV": 1e-09,
"TB_Reduced_Acquire": 1,
"TB_Reduced_Transmit": 1,
"TB_Drug_Cure_Rate_HIV": 0,
"TB_Drug_Cure_Rate_MDR": 0
}
}
}
|
TB_Reduced_Transmit |
array of floats |
0 |
1 |
0 |
Proportion reduction in TB transmission under drug treatment. The value scales the Base_Infectivity parameter. |
{
"TBHIV_Drug_Params": {
"ACFDOTS": {
"TB_Drug_Cure_Rate": 0.25,
"TB_Drug_Inactivation_Rate": 1e-09,
"TB_Drug_Inactivation_Rate_HIV": 1e-09,
"TB_Drug_Inactivation_Rate_MDR": 1e-09,
"TB_Drug_Mortality_Rate": 1e-09,
"TB_Drug_Mortality_Rate_HIV": 1e-09,
"TB_Drug_Mortality_Rate_MDR": 1e-09,
"TB_Drug_Primary_Decay_Time_Constant": 179,
"TB_Drug_Relapse_Rate": 1e-09,
"TB_Drug_Relapse_Rate_HIV": 1e-09,
"TB_Drug_Relapse_Rate_MDR": 1e-09,
"TB_Drug_Resistance_Rate": 1e-09,
"TB_Drug_Resistance_Rate_HIV": 1e-09,
"TB_Reduced_Acquire": 1,
"TB_Reduced_Transmit": 1,
"TB_Drug_Cure_Rate_HIV": 0,
"TB_Drug_Cure_Rate_MDR": 0
}
}
}
|
Deprecated demographics parameters¶
ImmunityDistributionFlag, ImmunityDistribution1, and ImmunityDistribution2 were renamed to SusceptibilityDistributionFlag, SusceptibilityDistribution1, and SusceptibilityDistribution2. In previous versions of EMOD, the naming was counterintuitive to the functionality. For example, setting a value of 1 for the immunity indicated zero immunity/complete susceptibility. Now the parameters more accurately reflect that you are setting a susceptibility value. The functionality is the same.
Deprecated config parameters¶
Immunity_Transmission_Factor, Immunity_Mortality_Factor, and Immunity_Acquisition_Factor were renamed to Post_Infection_Transmission_Multiplier, Post_Infection_Mortality_Multiplier, and Post_Infection_Acquistion_Multiplier. The functionality is the same.
Deprecated campaign parameters¶
The TB_SIM simulation type has been deprecated and replaced with TBHIV_SIM, which does not include HIV transmission but adds the ability to model the effect of HIV coinfection on the spread of TB.
The following campaign classes, which have not yet been fully tested with the TBHIV simulation type, have been disabled:
HealthSeekingBehaviorUpdate
HealthSeekingBehaviorUpdateable
AntiTBPropDepDrug
SmearDiagnostic
In previous versions of EMOD, you could set the tendency of individuals to seek out health care using HealthSeekingBehaviorUpdateable and then update the value of the Tendency parameter using HealthSeekingBehaviorUpdate. Now, you use individual properties to update individuals when they receive the SimpleHealthSeekingBehavior intervention, as you would to control the flow of individuals through other intervention classes. For example, you could create an individual property with HSBold and HSBnew values in the demographics file and assign all individuals to HSBold. Then you could distribute the first SimpleHealthSeekingBehavior (with one Tendency value) to all HSBold individuals and use New_Property_Value to assign them to HSBnew after receiving the intervention. The next SimpleHealthSeekingBehavior intervention (with a different Tendency value) could be distributed, setting Disqualifying_Properties to HSBold and, if desired, using New_Property_Value to reassign HSBold to those individuals.
Similarly, AntiTBPropDepDrug was disabled and superseded with TBHIVConfigurableTBDrug, which allows for drug effects based on HIV status and where dependence on IndividualProperties is configured through Property_Restrictions. In addition, AntiTBPropDepDrub can be replaced with AntiTBDrug, also using Property_Restrictions and new property values to target particular individuals with drug interventions for tuberculosis without HIV coinfections.
SmearDiagnostic was disabled and can be replaced with DiagnosticTreatNeg. While SmearDiagnostic would only broadcast when an individual had a positive smear diagnostic, DiagnosticTreatNeg has the added benefit of broadcasting negative and default diagnostic test events.
TB_Drug_Clearance_Rate_HIV and TB_Drug_Clearance_Rate_MDR parameters have been renamed to TB_Drug_Cure_Rate_HIV and TB_Drug_Cure_Rate_MDR.
Error messages¶
When attempting to run an intervention using one of the disabled tuberculosis classes, such as AntiTBPropDepDrug, HealthSeekingBehaviorUpdate, HealthSeekingBehaviorUpdateable, and SmearDiagnostic, you will receive an error similar to the following: “00:00:01 [0] [I] [JsonConfigurable] Using the default value ( “Intervention_Name” : “HealthSeekingBehaviorUpdateable” ) for unspecified parameter. 00:00:02 [0] [E] [Eradication] 00:00:02 [0] [E] [Eradication] GeneralConfigurationException: Exception in SimulationEventContext.cpp at 242 in Kernel::SimulationEventContextHost::LoadCampaignFromFile. Array out of bounds”
Note
These campaign classes have been disabled because they have not yet been fully tested with the TBHIV simulation type.
EMOD schema and simulation types¶
In the schema for the Simulation_Type parameter the enum values list additional simulation types that are not supported by EMOD.
EMOD supports the following simulation types for modeling a variety of diseases:
Generic disease (GENERIC_SIM), which can be used for modeling a variety of diseases such as influenza or measles
Vector-borne diseases (VECTOR_SIM), which can be used for modeling vector-borne diseases such as dengue
Malaria (MALARIA_SIM), which adds features specific to malaria biology and treatment
Tuberculosis with HIV coinfection (TBHIV_SIM), which can be used for modeling TB transmission, with the option to add HIV coinfection as a contributing factor
Sexually transmitted infections (STI_SIM), which adds features for sexual relationship networks
HIV (HIV_SIM), which adds features specific to HIV biology and treatment
Environmental transmission (ENVIRONMENTAL_SIM), which adds features for diseases transmitted through contaminated food or water
Typhoid (TYPHOID_SIM), which adds features specific to typhoid biology and treatment
For information about building the schema, see Generate a list of all available parameters (a schema).
EMOD v2.13¶
The EMOD v2.13 release includes many new features for all supported simulation types.
New configuration parameters¶
For the malaria simulation type, the following new configuration parameters are available:
Parameter |
Data type |
Minimum |
Maximum |
Default |
Description |
Example |
|---|---|---|---|---|---|---|
Custom_Reports_Filename |
string |
NA |
NA |
UNINITIALIZED STRING |
The name of the file containing custom report configuration parameters. Omitting this parameter or setting it to RunAllCustomReports will load all reporters found that are valid for the given simulation type. The file must be in JSON format. |
{
"Custom_Reports_Filename": "custom_reports.json"
}
|
Cycle_Arrhenius_1 |
float |
0 |
1.00E+15 |
4.09E+10 |
The Arrhenius equation, \(a_1^{-a_2/T}\), with T in degrees Kelvin, parameterizes the mosquito feeding cycle rate. This duration is a decreasing function of temperature. The variable a1 is a temperature-independent scale factor on feeding rate. Temperature_Dependent_Feeding_Cycle must be set to ARRHENIUS_DEPENDENCE. |
{
"Temperature_Dependent_Feeding_Cycle": "ARRHENIUS_DEPENDENCE",
"Vector_Species_Params": {
"arabiensis": {
"Cycle_Arrhenius_1": 99,
"Cycle_Arrhenius_2": 88
}
}
}
|
Cycle_Arrhenius_2 |
float |
0 |
1.00E+15 |
7740 |
The Arrhenius equation, \(a_1^{-a_2/T}\), with T in degrees Kelvin, parameterizes the mosquito feeding cycle rate. This duration is a decreasing function of temperature. The variable a2 is a temperature-independent scale factor on feeding rate. Temperature_Dependent_Feeding_Cycle must be set to ARRHENIUS_DEPENDENCE. |
{
"Temperature_Dependent_Feeding_Cycle": "ARRHENIUS_DEPENDENCE",
"Vector_Species_Params": {
"arabiensis": {
"Cycle_Arrhenius_1": 99,
"Cycle_Arrhenius_2": 88
}
}
}
|
Cycle_Arrhenius_Reduction_Factor |
float |
0 |
1 |
1 |
The scale factor applied to cycle duration (from oviposition to oviposition) to reduce the duration when primary follicles are at stage II rather than I in the case of newly emerged females. Temperature_Dependent_Feeding_Cycle must be set to ARRHENIUS_DEPENDENCE. |
{
"Temperature_Dependent_Feeding_Cycle": "ARRHENIUS_DEPENDENCE",
"Vector_Species_Params": {
"funestus": {
"Cycle_Arrhenius_Reduction_Factor": 0.44
}
}
}
|
Drought_Egg_Hatch_Delay |
float |
0 |
1 |
0.33 |
Proportion of regular egg hatching that still occurs when habitat dries up. Enable_Drought_Egg_Hatch_Delay must be set to 1. |
{
"Enable_Drought_Egg_Hatch_Delay": 1,
"Drought_Egg_Hatch_Delay": 0.33
}
|
Egg_Arrhenius1 |
float |
0 |
1.00E+10 |
6.16E+07 |
The Arrhenius equation, math:a_1^{-a_2/T}, with T in degrees Kelvin, parameterizes the daily rate of mosquito egg hatching. This duration is a decreasing function of temperature. The variable a1 is a temperature-independent scale factor on hatching rate. Enable_Temperature_Dependent_Egg_Hatching must be set to 1. |
{
"Enable_Temperature_Dependent_Egg_Hatching": 1,
"Egg_Arrhenius1": 61599956,
"Egg_Arrhenius2": 5754
}
|
Egg_Arrhenius2 |
float |
0 |
1.00E+10 |
5754.03 |
The Arrhenius equation, \(a_1^{-a_2/T}\), with T in degrees Kelvin, parameterizes the daily rate of mosquito egg hatching. This duration is a decreasing function of temperature. The variable a2 is a temperature-dependent scale factor on hatching rate. Enable_Temperature_Dependent_Egg_Hatching must be set to 1. |
{
"Enable_Temperature_Dependent_Egg_Hatching": 1,
"Egg_Arrhenius1": 61599956,
"Egg_Arrhenius2": 5754
}
|
Egg_Hatch_Density_Dependence |
enum |
NA |
NA |
NO_DENSITY_DEPENDENCE |
The effect of larval density on egg hatching rate. Possible values are:
|
{
"Egg_Hatch_Density_Dependence": "NO_DENSITY_DEPENDENCE"
}
|
Enable_Drought_Egg_Hatch_Delay |
boolean |
0 |
1 |
0 |
Controls whether or not eggs hatch at delayed rates, set by Drought_Egg_Hatch_Delay, when the habitat dries up completely. |
{
"Enable_Drought_Egg_Hatch_Delay": 1,
"Drought_Egg_Hatch_Delay": 0.33
}
|
Enable_Egg_Mortality |
boolean |
0 |
1 |
0 |
Controls whether or not to include a daily mortality rate on the egg population, which is independent of climatic factors. |
{
"Enable_Egg_Mortality": 1,
}
|
Enable_Temperature_Dependent_Egg_Hatching |
boolean |
0 |
1 |
0 |
Controls whether or not temperature has an effect on egg hatching, defined by Egg_Arrhenius_1 and Egg_Arrhenius_2. |
{
"Enable_Temperature_Dependent_Egg_Hatching": 1,
"Egg_Arrhenius1": 61599956.864,
"Egg_Arrhenius2": 5754.033
}
|
Enable_Vector_Aging |
boolean |
0 |
1 |
0 |
Controls whether or not vectors undergo senescence as they age. |
{
"Enable_Vector_Aging": 1
}
|
Incubation_Period_Log_Mean |
float |
0 |
3.40E+38 |
6 |
The mean of log normal for the incubation period distribution. Incubation_Period_Distribution must be set to LOG_NORMAL_DURATION. |
{
"Incubation_Period_Distribution": "LOG_NORMAL_DURATION",
"Incubation_Period_Log_Mean": 5.758,
"Incubation_Period_Log_Width": 0.27
}
|
Incubation_Period_Log_Width |
float |
0 |
3.40E+38 |
1 |
The log width of log normal for the incubation period distribution. Incubation_Period_Distribution must be set to LOG_NORMAL_DURATION. |
{
"Incubation_Period_Distribution": "LOG_NORMAL_DURATION",
"Incubation_Period_Log_Mean": 5.758,
"Incubation_Period_Log_Width": 0.27
}
|
Infectivity_Exponential_Baseline |
float |
0 |
1 |
0 |
The scale factor applied to Base_Infectivity at the beginning of a simulation, before the infectivity begins to grow exponentially. Infectivity_Scale_Type must be set to EXPONENTIAL_FUNCTION_OF_TIME. |
{
"Infectivity_Exponential_Baseline": 0.1,
"Infectivity_Exponential_Delay": 90,
"Infectivity_Exponential_Rate": 45,
"Infectivity_Scale_Type": "EXPONENTIAL_FUNCTION_OF_TIME"
}
|
Infectivity_Exponential_Delay |
float |
0 |
3.40E+38 |
0 |
The number of days before infectivity begins to ramp up exponentially. Infectivity_Scale_Type must be set to EXPONENTIAL_FUNCTION_OF_TIME. |
{
"Infectivity_Exponential_Baseline": 0.1,
"Infectivity_Exponential_Delay": 90,
"Infectivity_Exponential_Rate": 45,
"Infectivity_Scale_Type": "EXPONENTIAL_FUNCTION_OF_TIME"
}
|
Infectivity_Exponential_Rate |
float |
0 |
3.40E+38 |
0 |
The daily rate of exponential growth to approach to full infectivity after the delay set by Infectivity_Exponential_Delay has passed. Infectivity_Scale_Type must be set to EXPONENTIAL_FUNCTION_OF_TIME. |
{
"Infectivity_Exponential_Rate": 45
}
|
Memory_Usage_Halting_Threshold_Working_Set_MB |
integer |
0 |
1.00E+06 |
8000 |
The maximum size (in MB) of working set memory before the system throws an exception and halts. |
{
"Memory_Usage_Halting_Threshold_Working_Set_MB": 4000
}
|
Memory_Usage_Warning_Threshold_Working_Set_MB |
integer |
0 |
1.00E+06 |
7000 |
The maximum size (in MB) of working set memory before memory usage statistics are written to the log regardless of log level. |
{
"Memory_Usage_Warning_Threshold_Working_Set_MB": 3500
}
|
Nighttime_Feeding_Fraction |
float |
0 |
1 |
1 |
The fraction of feeds on humans (for a specific mosquito species) that occur during the nighttime. Thus the fraction of feeds on humans that occur during the day equals 1 - (value of this parameter). |
{
"Vector_Species_Params": {
"arabiensis": {
"Acquire_Modifier": 0.2,
"Adult_Life_Expectancy": 10,
"Anthropophily": 0.95,
"Aquatic_Arrhenius_1": 84200000000,
"Aquatic_Arrhenius_2": 8328,
"Aquatic_Mortality_Rate": 0.1,
"Cycle_Arrhenius_1": 0,
"Cycle_Arrhenius_2": 0,
"Cycle_Arrhenius_Reduction_Factor": 0,
"Days_Between_Feeds": 3,
"Egg_Batch_Size": 100,
"Immature_Duration": 4,
"Indoor_Feeding_Fraction": 0.5,
"Infected_Arrhenius_1": 117000000000,
"Infected_Arrhenius_2": 8336,
"Infected_Egg_Batch_Factor": 0.8,
"Infectious_Human_Feed_Mortality_Factor": 1.5,
"Larval_Habitat_Types": {
"TEMPORARY_RAINFALL": 11250000000
},
"Nighttime_Feeding_Fraction": 1,
"Transmission_Rate": 0.5
}
}
}
|
Serialization_Time_Steps |
array of integers |
0 |
2.15E+09 |
The list of time steps after which to save the serialized state. 0 (zero) indicates the initial state before simulation, n indicates after the nth time step. By default, no serialized state is saved. |
{
"Serialization_Time_Steps": [
0,
10
]
}
|
|
Serialized_Population_Filenames |
array of strings |
NA |
NA |
NA |
Array of filenames with serialized population data. The number of filenames must match the number of cores used for the simulation. The file must be in .dtk format. |
{
"Serialized_Population_Filenames": [
"state-00010.dtk"
]
}
|
Serialized_Population_Path |
string |
NA |
NA |
. |
The root path for the serialized population files. |
{
"Serialized_Population_Path": "../00_Generic_Version_1_save/output"
}
|
Temperature_Dependent_Feeding_Cycle |
enum |
NA |
NA |
NO_TEMPERATURE_DEPENDENCE |
The effect of temperature on the duration between blood feeds. Possible values are:
|
{
"Temperature_Dependent_Feeding_Cycle": "BOUNDED_DEPENDENCE"
}
|
To view all available configuration parameters, see Configuration parameters.
New demographics parameters¶
In all simulation types, you can now assign properties like risk or quality of care to nodes using NodeProperties, which are configured much like IndividualProperties. In addition, a new property type is available for both nodes and individuals called InterventionStatus, which is used by the campaign file to distribute interventions based on the other interventions an individual or node has received. This property type was previously available only for individuals in the HIV simulation type and was known as the CascadeState. The relevant campaign parameters are described in the next section.
For more information, see the table below.
Parameter |
Data type |
Minimum |
Maximum |
Default |
Description |
Example |
|---|---|---|---|---|---|---|
NodeProperties |
array of objects |
NA |
NA |
NA |
An array that contains parameters that add properties to nodes in a simulation. For example, you can define values for intervention status, risk, and other properties and assign values to different nodes. |
{
"NodeProperties": [{
"Property": "Risk",
"Values": ["HIGH", "MEDIUM", "LOW"],
"Initial_Distribution": [0.1, 0.4, 0.5]
}]
}
|
Property |
enum |
NA |
NA |
NA |
The individual or node property type for which you will assign arbitrary values to create groups. You can then move individuals or nodes into or out of different groups or target interventions to particular groups. Possible values are:
|
{
"Defaults": {
"IndividualProperties": [{
"Property": "Age_Bin",
"Age_Bin_Edges_In_Years": [ 0, 6, 10, 20, -1 ]
}]
}
}
{
"NodeProperties": [{
"Property": "InterventionStatus",
"Values": ["NONE", "RECENT_SPRAY"],
"Initial_Distribution": [1.0, 0.0]
}]
}
|
New campaign parameters¶
The addition of NodeProperties in the demographics file also necessitated the addition of Node_Property_Restrictions to control how interventions are distributed based on the property values assigned to each node.
The new campaign parameters Disqualifying_Properties and New_Property_Value were added to every intervention to control how interventions are distributed based on properties assigned to individuals or nodes. Disqualifying_Properties prevents an intervention from being distributed to individuals or nodes with certain property values. New_Property_Value updates the property value after they receive an intervention.
These are generally used with the the property type InterventionStatus to control how interventions are distributed based on the interventions already received. For example, a household may be ineligible for clinical treatment for a length of time if they already received treatment during a drug campaign. This functionality was previously only available for individuals in the HIV simulation type and used parameters previously called Abort_States and Valid_Cascade_States.
The following event coordinators and intervention classes are new for this simulation type.
CommunityHealthWorkerEventCoordinator¶
The CommunityHealthWorkerEventCoordinator coordinator class is used to model a health care worker’s ability to distribute interventions to the nodes and individual in their coverage area. This coordinator distributes a limited number of interventions per day, and can create a backlog of individuals or nodes requiring the intervention. For example, individual-level interventions could be distribution of drugs and node-level interventions could be spraying houses with insecticide.
Parameter |
Data type |
Minimum |
Maximum |
Default |
Description |
Example |
|---|---|---|---|---|---|---|
Amount_In_Shipment |
integer |
1 |
2.15E+0 |
2.15E+09 |
The number of interventions (such as vaccine doses) that a health worker or clinic receives in a shipment. Interventions can only be distributed if they are in stock; stock is updated every Days_Between_Shipments with the Amount_In_Shipment. |
{
"Amount_In_Shipment": 10
}
|
Days_Between_Shipments |
float |
1 |
3.40E+3 |
3.40E+38 |
The number of days to wait before a clinic or health worker receives a new shipment of interventions (such as vaccine doses). Interventions can only be distributed if they are in stock; stock is updated every Days_Between_Shipments with the Amount_In_Shipment. |
{
"Days_Between_Shipments": 30
}
|
Demographic_Coverage |
float |
0 |
1 |
1 |
The fraction of individuals in the target demographic that will receive this intervention. |
{
"Demographic_Coverage": 1
}
|
Duration |
float |
0 |
3.40E+3 |
3.40E+38 |
The number of days for an event coordinator to be active before it expires. |
{
"Duration": 65
}
|
Initial_Amount_Constant |
float |
0 |
3.40282E+38 |
6 |
The initial amount to use for all health workers when Initial_Amount_Distribution is set to CONSTANT_DISTRIBUTION. |
{
"Initial_Amount_Distribution": "CONSTANT_DISTRIBUTION",
"Initial_Amount_Constant": 8
}
|
Initial_Amount_Distribution |
enum |
NA |
NA |
NOT_INITIALIZED |
The distribution type to use for assigning the initial amount of interventions in stock. Each assigned value is a random draw from the distribution. Possible values are:
|
{
"Initial_Amount_Distribution": "DUAL_EXPONENTIAL_DISTRIBUTION",
"Initial_Amount_Mean_1": 4,
"Initial_Amount_Mean_2": 12,
"Initial_Amount_Proportion_1": 0.2
}
|
Initial_Amount_Exponential |
float |
0 |
3.40282E+38 |
6 |
The mean of the initial amount of intervention in stock when Initial_Amount_Distribution is set to EXPONENTIAL_DISTRIBUTION. |
{
"Initial_Amount_Distribution": "EXPONENTIAL_DISTRIBUTION",
"Initial_Amount_Exponential": 4.25
}
|
Initial_Amount_Gaussian_Mean |
float |
0 |
3.40282E+38 |
6 |
The mean of the initial amount of intervention in stock when Initial_Amount_Distribution is set to GAUSSIAN_DISTRIBUTION. |
{
"Initial_Amount_Distribution": "GAUSSIAN_DISTRIBUTION",
"Initial_Amount_Gaussian_Mean": 8,
"Initial_Amount_Gaussian_Std_Dev": 1.5
}
|
Initial_Amount_Gaussian_Std_Dev |
float |
1.17549E-38 |
3.40282E+38 |
1 |
The standard deviation of the initial amount of intervention in stock when Initial_Amount_Distribution is set to GAUSSIAN_DISTRIBUTION. |
{
"Initial_Amount_Distribution": "GAUSSIAN_DISTRIBUTION",
"Initial_Amount_Gaussian_Mean": 8,
"Initial_Amount_Gaussian_Std_Dev": 1.5
}
|
Initial_Amount_Kappa |
float |
1.17549E-38 |
3.40282E+38 |
1 |
The shape value for the initial amount of intervention in stock when Initial_Amount_Distribution is set to WEIBULL_DISTRIBUTION. |
{
"Initial_Amount_Distribution": "WEIBULL_DISTRIBUTION",
"Initial_Amount_Kappa": 0.9,
"Initial_Amount_Lambda": 1.5
}
|
Initial_Amount_Lambda |
float |
1.17549E-38 |
3.40282E+38 |
1 |
The scale value for the initial amount of intervention in stock when Initial_Amount_Distribution is set to WEIBULL_DISTRIBUTION. |
{
"Initial_Amount_Distribution": "WEIBULL_DISTRIBUTION",
"Initial_Amount_Kappa": 0.9,
"Initial_Amount_Lambda": 1.5
}
|
Initial_Amount_Log_Normal_Mu |
float |
-3.40282e+38 |
3.40282E+38 |
6 |
The mean of the natural log of the initial amount of intervention in stock when Initial_Amount_Distribution is set to LOG_NORMAL_DISTRIBUTION. |
{
"Initial_Amount_Distribution": "LOG_NORMAL_DISTRIBUTION",
"Initial_Amount_Log_Normal_Mu": 9,
"Initial_Amount_Log_Normal_Sigma": 2
}
|
Initial_Amount_Log_Normal_Sigma |
float |
-3.40282e+38 |
3.40282E+38 |
1 |
The standard deviation of the natural log of the initial amount of intervention in stock when Initial_Amount_Distribution is set to LOG_NORMAL_DISTRIBUTION. |
{
"Initial_Amount_Distribution": "LOG_NORMAL_DISTRIBUTION",
"Initial_Amount_Log_Normal_Mu": 9,
"Initial_Amount_Log_Normal_Sigma": 2
}
|
Initial_Amount_Max |
float |
0 |
3.40282E+38 |
1 |
The maximum initial amount of intervention in stock when Initial_Amount_Distribution is set to UNIFORM_DISTRIBUTION. |
{
"Initial_Amount_Distribution": "UNIFORM_DISTRIBUTION",
"Initial_Amount_Min": 2,
"Initial_Amount_Max": 7
}
|
Initial_Amount_Mean_1 |
float |
1.17549E-38 |
3.40282E+38 |
1 |
The mean of the first exponential distribution when Initial_Amount_Distribution is set to DUAL_EXPONENTIAL_DISTRIBUTION. |
{
"Initial_Amount_Distribution": "DUAL_EXPONENTIAL_DISTRIBUTION",
"Initial_Amount_Mean_1": 4,
"Initial_Amount_Mean_2": 12,
"Initial_Amount_Proportion_1": 0.2
}
|
Initial_Amount_Mean_2 |
float |
1.17549E-38 |
3.40282E+38 |
1 |
The mean of the second exponential distribution when Initial_Amount_Distribution is set to DUAL_EXPONENTIAL_DISTRIBUTION. |
{
"Initial_Amount_Distribution": "DUAL_EXPONENTIAL_DISTRIBUTION",
"Initial_Amount_Mean_1": 4,
"Initial_Amount_Mean_2": 12,
"Initial_Amount_Proportion_1": 0.2
}
|
Initial_Amount_Min |
float |
0 |
3.40282E+38 |
0 |
The minimum of initial amount of intervention in stock when Initial_Amount_Distribution is set to UNIFORM_DISTRIBUTION. |
{
"Initial_Amount_Distribution": "UNIFORM_DISTRIBUTION",
"Initial_Amount_Min": 2,
"Initial_Amount_Max": 7
}
|
Initial_Amount_Peak_2_Value |
float |
0 |
3.40282E+38 |
1 |
The initial amount in stock to assign to the remaining health workers when Initial_Amount_Distribution is set to DUAL_CONSTANT_DISTRIBUTION. |
{
"Initial_Amount_Distribution": "DUAL_CONSTANT_DISTRIBUTION",
"Initial_Amount_Proportion_0": 0.25,
"Initial_Amount_Peak_2_Value": 5
}
|
Initial_Amount_Poisson_Mean |
float |
0 |
3.40282E+38 |
6 |
The mean of the initial amount of intervention in stock when Initial_Amount_Distribution is set to the POISSON_DISTRIBUTION. |
{
"Initial_Amount_Distribution": "POISSON_DISTRIBUTION",
"Initial_Amount_Poisson_Mean": 5
}
|
Initial_Amount_Proportion_0 |
float |
0 |
1 |
1 |
The proportion of health workers to assign a value of zero stock when Initial_Amount_Distribution is set to DUAL_CONSTANT_DISTRIBUTION. |
{
"Initial_Amount_Distribution": "DUAL_CONSTANT_DISTRIBUTION",
"Initial_Amount_Proportion_0": 0.25,
"Initial_Amount_Peak_2_Value": 5
}
|
Initial_Amount_Proportion_1 |
float |
0 |
1 |
1 |
The proportion of health workers in the first exponential distribution when Initial_Amount_Distribution is set to DUAL_EXPONENTIAL_DISTRIBUTION. |
{
"Initial_Amount_Distribution": "DUAL_EXPONENTIAL_DISTRIBUTION",
"Initial_Amount_Mean_1": 4,
"Initial_Amount_Mean_2": 12,
"Initial_Amount_Proportion_1": 0.2
}
|
Intervention_Config |
JSON object |
NA |
NA |
NA |
The nested JSON of the actual intervention to be distributed by this event coordinator. |
{
"Intervention_Config": {
"class": "BroadcastEvent",
"Broadcast_Event": "EventFromIntervention"
}
}
|
Max_Distributed_Per_Day |
integer |
1 |
2.15E+0 |
2.15E+09 |
The maximum number of interventions (such as vaccine doses) that can be distributed by health workers or clinics in a given day. |
{
"Max_Distributed_Per_Day": 1
}
|
Max_Stock |
integer |
0 |
2.15E+0 |
2.15E+09 |
The maximum number of interventions (such as vaccine doses) that can be stored by a health worker or clinic. If the amount of interventions in a new shipment and current stock exceeds this value, only the number of interventions specified by this value will be stored. |
{
"Max_Stock": 12
}
|
Node_Property_Restrictions |
array of JSON objects |
NA |
NA |
NA |
A list of the NodeProperty key:value pairs, as defined in the demographics file, that nodes must have to be targeted by the intervention. See NodeProperties and IndividualProperties parameters for more information. You can specify AND and OR combinations of key:value pairs with this parameter. |
The following example restricts the intervention to nodes that are urban and medium risk or rural and low risk. {
"Node_Property_Restrictions": [
{
"Place": "URBAN",
"Risk": "MED"
},
{
"Place": "RURAL",
"Risk": "LOW"
}
]
}
|
Property_Restrictions |
array of JSON objects |
NA |
NA |
NA |
A list of the IndividualProperty key:value pairs, as defined in the demographics file, that individuals must have to be targeted by this intervention. See NodeProperties and IndividualProperties parameters for more information. To specify AND and OR combinations of key:value pairs, use Property_Restrictions_Within_Node. You cannot use both of these parameters in the same event coordinator. |
{
"Property_Restrictions": [
"Risk:HIGH"
]
}
|
Property_Restrictions_Within_Node |
array of JSON objects |
NA |
NA |
NA |
A list of the IndividualProperty key:value pairs, as defined in the demographics file, that individuals must have to be targeted by this intervention. See NodeProperties and IndividualProperties parameters for more information. This parameter allows you to specify AND and OR combinations of key:value pairs. You may specify individual property restrictions using either this parameter or Property_Restrictions, but not both. |
The following example restricts the intervention to individuals who are urban and high risk or urban and medium risk. {
"Property_Restrictions_Within_Node": [
{
"Risk": "HIGH",
"Geographic": "URBAN"
},
{
"Risk": "MEDIUM",
"Geographic": "URBAN"
}
]
}
|
Target_Age_Min |
float |
0 |
3.40E+3 |
0 |
The lower end of ages targeted for an intervention, in years. Used when Target_Demographic is set to ExplicitAgeRanges or ExplicitAgeRangesAndGender. |
{
"Target_Age_Max": 20,
"Target_Age_Min": 10,
"Target_Demographic": "ExplicitAgeRanges"
}
|
Target_Demographic |
enum |
NA |
NA |
Everyone |
The target demographic group. Possible values are:
|
{
"Target_Age_Max": 20,
"Target_Age_Min": 10,
"Target_Demographic": "ExplicitAgeRanges"
}
|
Target_Gender |
enum |
NA |
NA |
All |
Specifies the gender restriction for the intervention. Possible values are:
|
{
"Target_Gender": "Male"
}
|
Target_Residents_Only |
boolean |
0 |
1 |
0 |
When set to true (1), the intervention is only distributed to individuals that began the simulation in the node (i.e. those that claim the node as their residence). |
{
"Target_Residents_Only": 1
}
|
Trigger_Condition_List |
array of strings |
NA |
NA |
NA |
The list of events that are of interest to the community health worker (CHW). If one of these events occurs, the individual or node is put into a queue to receive the CHW’s intervention. The CHW processes the queue when the event coordinator is updated. See Event list for possible values. |
{
"Trigger_Condition_List": [
"ListenForEvent"
]
}
|
Waiting_Period |
float |
0 |
3.40E+3 |
3.40E+38 |
The number of days a person or node can be in the queue waiting to get the intervention from the community health worker (CHW). If a person or node is in the queue, they will not be re-added to the queue if the event that would add them to the queue occurs. This allows them to maintain their priority, however they could be removed from the queue due to this waiting period. |
{
"Waiting_Period": 15
}
|
ImportPressure¶
The ImportPressure intervention class extends the ImportCases outbreak event. Rather than importing a deterministic number of cases on a scheduled day, ImportPressure applies a set of per-day rates of importation of infected individuals, over a corresponding set of durations. ImportPressure inherits from Outbreak; the Antigen and Genome parameters are defined as they are for all Outbreak events.
Parameter |
Data type |
Minimum |
Maximum |
Default |
Description |
Example |
|---|---|---|---|---|---|---|
Antigen |
integer |
0 |
10 |
0 |
The antigenic base strain ID of the outbreak infection. This must not exceed the number specified in the configuration parameter Number_Basestrains. |
{
"Intervention_Config": {
"Antigen": 0,
"Genome": 0,
"Outbreak_Source": "PrevalenceIncrease",
"class": "OutbreakIndividual"
}
}
|
Daily_Import_Pressures |
array of floats |
0 |
3.40E+3 |
0 |
The rate of per-day importation for each node that the intervention is distributed to. |
{
"Intervention_Config": {
"Antigen": 0,
"Genome": 0,
"Durations": [
100,
100,
100,
100,
100,
100,
100
],
"Daily_Import_Pressures": [
0.1,
5.0,
0.2,
1.0,
2.0,
0.0,
10.0
],
"class": "ImportPressure"
}
}
|
Durations |
array of integers |
0 |
2.15E+0 |
1 |
The durations over which to apply import pressure. |
{
"Intervention_Config": {
"Antigen": 0,
"Genome": 0,
"Durations": [
100,
100,
100,
100,
100,
100,
100
],
"Daily_Import_Pressures": [
0.1,
5.0,
0.2,
1.0,
2.0,
0.0,
10.0
],
"class": "ImportPressure"
}
}
|
Genome |
integer |
-1 |
16777216 |
0 |
The genetic substrain ID of the outbreak infection. This must not exceed the number specified in the configuration parameter Number_Substrains. |
{
"Intervention_Config": {
"Antigen": 0,
"Genome": 0,
"Outbreak_Source": "PrevalenceIncrease",
"class": "OutbreakIndividual",
"Incubation_Period_Override": 0
}
}
|
Import_Age |
float |
0 |
43800 |
365 |
The age (in days) of infected import cases. |
{
"Import_Age": 10000
}
|
Incubation_Period_Override |
integer |
-1 |
2.15E+0 |
-1 |
The incubation period, in days, that infected individuals will go through before becoming infectious. This value overrides the incubation period set in the configuration file. Set to -1 to honor the configuration parameter settings. |
{
"Incubation_Period_Override": 0
}
|
Number_Cases_Per_Node |
integer |
0 |
2.15E+0 |
1 |
The number of new cases of Outbreak to import (per node). Note This will increase the population and there is no control over demographics of these individuals. |
{
"Intervention_Config": {
"Antigen": 0,
"Genome": 0,
"Outbreak_Source": "ImportCases",
"Number_Cases_Per_Node": 10,
"class": "Outbreak"
}
}
|
Probability_Of_Infection |
float |
0 |
1 |
1 |
The probability that each individual added by the intervention is infected. 0.0 adds only susceptible individuals to the population. |
{
"Probability_Of_Infection": 1
}
|
IndividualImmunityChanger¶
The IndividualImmunityChanger intervention class acts essentially as a MultiEffectVaccine, with the exception of how the behavior is implemented. Rather than attaching a persistent vaccine intervention object to an individual’s intervention list (as a campaign-individual-multieffectboostervaccine does), the IndividualImmunityChanger directly alters the immune modifiers of the individual’s susceptibility object and is then immediately disposed of. Any immune waning is not governed by Waning effect classes, as MultiEffectVaccine is, but rather by the immunity waning parameters in the configuration file.
Parameter |
Data type |
Minimum |
Maximum |
Default |
Description |
Example |
|---|---|---|---|---|---|---|
Boost_Acquire |
float |
0 |
1 |
0 |
Specifies the boosting effect on acquisition immunity for naive individuals (without natural or vaccine-derived immunity) for a multi-effect booster vaccine. This does not replace current immunity, it builds multiplicatively on top of it. |
{
"Boost_Acquire": 0.7
}
|
Boost_Mortality |
float |
0 |
1 |
0 |
Specifies the boosting effect on mortality immunity for naive individuals (without natural or vaccine-derived immunity) for a multi-effect booster vaccine. This does not replace current immunity, it builds multiplicatively on top of it. |
{
"Boost_Mortality": 1.0
}
|
Boost_Threshold_Acquire |
float |
0 |
1 |
0 |
Specifies how much acquisition immunity is required before the vaccine changes from a prime to a boost. |
{
"Boost_Threshold_Acquire": 0.0
}
|
Boost_Threshold_Mortality |
float |
0 |
1 |
0 |
Specifies how much mortality immunity is required before the vaccine changes from a prime to a boost. |
{
"Boost_Threshold_Mortality": 0.0
}
|
Boost_Threshold_Transmit |
float |
0 |
1 |
0 |
Specifies how much transmission immunity is required before the vaccine changes from a prime to a boost. |
{
"Boost_Threshold_Transmit": 0.0
}
|
Boost_Transmit |
float |
0 |
1 |
0 |
Specifies the boosting effect on transmission immunity for naive individuals (without natural or vaccine-derived immunity) for a multi-effect booster vaccine. This does not replace current immunity, it builds multiplicatively on top of it. |
{
"Boost_Transmit": 0.5
}
|
Cost_To_Consumer |
float |
0 |
999999 |
10 |
The unit cost per vaccine (unamortized). |
{
"Cost_To_Consumer": 10.0
}
|
Prime_Acquire |
float |
0 |
1 |
0 |
Specifies the priming effect on acquisition immunity for naive individuals (without natural or vaccine-derived immunity) for a multi-effect booster vaccine. |
{
"Prime_Acquire": 0.1
}
|
Prime_Mortality |
float |
0 |
1 |
0 |
Specifies the priming effect on mortality immunity for naive individuals (without natural or vaccine-derived immunity) for a multi-effect booster vaccine. |
{
"Prime_Mortality": 0.3
}
|
Prime_Transmit |
float |
0 |
1 |
0 |
Specifies the priming effect on transmission immunity for naive individuals (without natural or vaccine-derived immunity) for a multi-effect booster vaccine. |
{
"Prime_Transmit": 0.2
}
|
MultiEffectBoosterVaccine¶
The MultiEffectBoosterVaccine intervention class is derived from MultiEffectVaccine and preserves many of the same parameters. Upon distribution and successful take, the vaccine’s effect in each immunity compartment (acquisition, transmission, and mortality) is determined by the recipient’s immune state. If the recipient’s immunity modifier in the corresponding compartment is above a user-specified threshold, then the vaccine’s initial effect will be equal to the corresponding priming parameter. If the recipient’s immune modifier is below this threshold, then the vaccine’s initial effect will be equal to the corresponding boost parameter. After distribution, the effect wanes, just like a MultiEffectVaccine. The behavior is intended to mimic biological priming and boosting.
Parameter |
Data type |
Minimum |
Maximum |
Default |
Description |
Example |
|---|---|---|---|---|---|---|
Acquire_Config |
JSON object |
NA |
NA |
NA |
The configuration for multi-effect vaccine acquisition. Specify how this effect decays over time using one of the Waning effect classes. |
{
"Acquire_Config": {
"Initial_Effect": 0.9,
"Decay_Time_Constant": 2525,
"class": "WaningEffectExponential"
}
}
|
Boost_Acquire |
float |
0 |
1 |
0 |
Specifies the boosting effect on acquisition immunity for naive individuals (without natural or vaccine-derived immunity) for a multi-effect booster vaccine. This does not replace current immunity, it builds multiplicatively on top of it. |
{
"Boost_Acquire": 0.7
}
|
Boost_Mortality |
float |
0 |
1 |
0 |
Specifies the boosting effect on mortality immunity for naive individuals (without natural or vaccine-derived immunity) for a multi-effect booster vaccine. This does not replace current immunity, it builds multiplicatively on top of it. |
{
"Boost_Mortality": 1.0
}
|
Boost_Threshold_Acquire |
float |
0 |
1 |
0 |
Specifies how much acquisition immunity is required before the vaccine changes from a prime to a boost. |
{
"Boost_Threshold_Acquire": 0.0
}
|
Boost_Threshold_Mortality |
float |
0 |
1 |
0 |
Specifies how much mortality immunity is required before the vaccine changes from a prime to a boost. |
{
"Boost_Threshold_Mortality": 0.0
}
|
Boost_Threshold_Transmit |
float |
0 |
1 |
0 |
Specifies how much transmission immunity is required before the vaccine changes from a prime to a boost. |
{
"Boost_Threshold_Transmit": 0.0
}
|
Boost_Transmit |
float |
0 |
1 |
0 |
Specifies the boosting effect on transmission immunity for naive individuals (without natural or vaccine-derived immunity) for a multi-effect booster vaccine. This does not replace current immunity, it builds multiplicatively on top of it. |
{
"Boost_Transmit": 0.5
}
|
Cost_To_Consumer |
float |
0 |
999999 |
10 |
The unit cost per vaccine (unamortized). |
{
"Cost_To_Consumer": 10.0
}
|
Disqualifying_Properties |
array of strings |
NA |
NA |
[] |
A list of IndividualProperty key:value pairs that cause an intervention to be aborted (persistent interventions will stop being distributed to individuals with these values). See NodeProperties and IndividualProperties parameters for more information. Generally used to control the flow of health care access. For example, to prevent the same individual from accessing health care via two different routes at the same time. |
{
"Disqualifying_Properties": [
"InterventionStatus:LostForever"
]
}
|
Dont_Allow_Duplicates |
boolean |
0 |
1 |
0 |
If an individual’s container has an intervention, set to true (1) to prevent them from receiving another copy of the intervention. Supported by all intervention classes. |
{
"Dont_Allow_Duplicates": 0
}
|
Intervention_Name |
string |
NA |
NA |
NA |
The optional name used to refer to this intervention as a means to differentiate it from others that use the same class. |
{
"Intervention_Config": {
"class": "MultiEffectBoosterVaccine",
"Intervention_Name": "Tetanus booster shot"
}
}
|
Mortality_Config |
JSON object |
NA |
NA |
NA |
The configuration for multi-effect vaccine mortality. Specify how this effect decays over time using one of the Waning effect classes. |
{
"Mortality_Config": {
"Initial_Effect": 1.0,
"Decay_Time_Constant": 2525,
"class": "WaningEffectExponential"
}
}
|
New_Property_Value |
string |
NA |
NA |
NA |
An optional IndividualProperty key:value pair that will be assigned when the intervention is distributed. See NodeProperties and IndividualProperties parameters for more information. Generally used to indicate the broad category of health care cascade to which an intervention belongs to prevent individuals from accessing care through multiple pathways. For example, if an individual must already be taking a particular medication to be prescribed a new one. |
{
"New_Property_Value": "InterventionStatus:None"
}
|
Prime_Acquire |
float |
0 |
1 |
0 |
Specifies the priming effect on acquisition immunity for naive individuals (without natural or vaccine-derived immunity) for a multi-effect booster vaccine. |
{
"Prime_Acquire": 0.1
}
|
Prime_Mortality |
float |
0 |
1 |
0 |
Specifies the priming effect on mortality immunity for naive individuals (without natural or vaccine-derived immunity) for a multi-effect booster vaccine. |
{
"Prime_Mortality": 0.3
}
|
Prime_Transmit |
float |
0 |
1 |
0 |
Specifies the priming effect on transmission immunity for naive individuals (without natural or vaccine-derived immunity) for a multi-effect booster vaccine. |
{
"Prime_Transmit": 0.2
}
|
Transmit_Config |
JSON object |
NA |
NA |
NA |
The configuration for multi-effect vaccine transmission. Specify how this effect decays over time using one of the Waning effect classes. |
{
"Transmit_Config": {
"Initial_Effect": 0.6,
"Decay_Time_Constant": 2525,
"class": "WaningEffectExponential"
}
}
|
Vaccine_Take |
float |
0 |
1 |
1 |
The rate at which delivered vaccines will successfully stimulate an immune response and achieve the desired efficacy. For example, if it is set to 0.9, there will be a 90 percent chance that the vaccine will start with the specified efficacy, and a 10 percent chance that it will have no efficacy at all. |
{
"Intervention_Config": {
"class": "SimpleVaccine",
"Cost_To_Consumer": 10,
"Vaccine_Type": "AcquisitionBlocking",
"Vaccine_Take": 1,
"Efficacy_Is_Multiplicative": 0,
"Waning_Config": {
"class": "WaningEffectConstant",
"Initial_Effect": 0.3
}
}
}
|
NodePropertyValueChanger¶
The NodePropertyValueChanger intervention class sets a given node property to a new value. You can also define a duration in days before the node property reverts back to its original value, the probability that a node will change its node property to the target value, and the number of days over which nodes will attempt to change their individual properties to the target value. This node-level intervention functions in a similar manner as the individual-level intervention, PropertyValueChanger.
Parameter |
Data type |
Minimum |
Maximum |
Default |
Description |
Example |
|---|---|---|---|---|---|---|
Daily_Probability |
float |
0 |
1 |
1 |
The daily probability that a node will move to the Target_Property_Value. |
{
"Intervention_Config": {
"class": "PropertyValueChanger",
"Disqualifying_Properties": [],
"New_Property_Value": "",
"Target_Property_Key": "Risk",
"Target_Property_Value": "LOW",
"Daily_Probability": 1.0,
"Maximum_Duration": 0,
"Revert": 0
}
}
|
Disqualifying_Properties |
array of strings |
NA |
NA |
[] |
A list of NodeProperty key:value pairs that cause an intervention to be aborted (persistent interventions will stop being distributed to nodes with these values). See NodeProperties and IndividualProperties parameters for more information. Generally used to control the flow of health care access. For example, to prevent the same individual from accessing health care via two different routes at the same time. |
{
"Disqualifying_Properties": [
"InterventionStatus:LostForever"
]
}
|
Intervention_Name |
string |
NA |
NA |
NA |
The optional name used to refer to this intervention as a means to differentiate it from others that use the same class. |
{
"Intervention_Name": "Diagnostic_Sample"
}
|
Maximum_Duration |
float |
-1 |
3.40E+38 |
3.40E+38 |
The maximum amount of time nodes have to update the property value. This timing works in conjunction with Daily_Probability. |
{
"Intervention_Config": {
"class": "PropertyValueChanger",
"Disqualifying_Properties": [],
"New_Property_Value": "",
"Target_Property_Key": "Risk",
"Target_Property_Value": "LOW",
"Daily_Probability": 1.0,
"Maximum_Duration": 0,
"Revert": 0
}
}
|
New_Property_Value |
string |
NA |
NA |
NA |
An optional NodeProperty key:value pair that will be assigned when the intervention is distributed. See NodeProperties and IndividualProperties parameters for more information. Generally used to indicate the broad category of health care cascade to which an intervention belongs to prevent individuals from accessing care through multiple pathways. For example, if an individual must already be taking a particular medication to be prescribed a new one. |
{
"New_Property_Value": "InterventionStatus:None"
}
|
Revert |
float |
0 |
10000 |
0 |
The number of days before an individual moves back to their original group. |
{
"Intervention_Config": {
"class": "PropertyValueChanger",
"Disqualifying_Properties": [],
"New_Property_Value": "",
"Target_Property_Key": "Risk",
"Target_Property_Value": "LOW",
"Daily_Probability": 1.0,
"Maximum_Duration": 0,
"Revert": 0
}
}
|
Target_NP_Key_Value |
string |
NA |
NA |
NA |
The NodeProperty key:value pair, as defined in the demographics file, to assign to the node. |
{
"Target_NP_Key_Value": "InterventionStatus:NONE"
}
|
SimpleBoosterVaccine¶
The SimpleBoosterVaccine intervention class is derived from SimpleVaccine and preserves many of the same parameters. The behavior is much like SimpleVaccine, except that upon distribution and successful take, the vaccine’s effect is determined by the recipient’s immune state. If the recipient’s immunity modifier in the corresponding channel (acquisition, transmission, or mortality) is above a user-specified threshold, then the vaccine’s initial effect will be equal to the corresponding priming parameter. If the recipient’s immune modifier is below this threshold, then the vaccine’s initial effect will be equal to the corresponding boosting parameter. After distribution, the effect wanes, just like SimpleVaccine. In essence, this intervention provides a SimpleVaccine intervention with one effect to all naive (below- threshold) individuals, and another effect to all primed (above-threshold) individuals; this behavior is intended to mimic biological priming and boosting.
Parameter |
Data type |
Minimum |
Maximum |
Default |
Description |
Example |
|---|---|---|---|---|---|---|
Boost_Effect |
float |
0 |
1 |
1 |
Specifies the boosting effect on [acquisition/transmission/mortality] immunity for previously exposed individuals (either natural or vaccine-derived). This does not replace current immunity, it builds multiplicatively on top of it. |
{
"Intervention_Config": {
"Cost_To_Consumer": 10.0,
"Vaccine_Take": 1,
"Vaccine_Type": "MortalityBlocking",
"Prime_Effect": 0.25,
"Boost_Effect": 0.45,
"Boost_Threshold": 0.0,
"Waning_Config": {
"Box_Duration": 10,
"Initial_Effect": 1,
"class": "WaningEffectBox"
},
"class": "SimpleBoosterVaccine"
}
}
|
Boost_Threshold |
float |
0 |
1 |
0 |
Specifies how much immunity is required before the vaccine changes from a priming effect to a boosting effect. |
{
"Intervention_Config": {
"Cost_To_Consumer": 10.0,
"Vaccine_Take": 1,
"Vaccine_Type": "MortalityBlocking",
"Prime_Effect": 0.25,
"Boost_Effect": 0.45,
"Boost_Threshold": 0.0,
"Waning_Config": {
"Box_Duration": 10,
"Initial_Effect": 1,
"class": "WaningEffectBox"
},
"class": "SimpleBoosterVaccine"
}
}
|
Cost_To_Consumer |
float |
0 |
999999 |
10 |
The unit cost per vaccine (unamortized). |
{
"Cost_To_Consumer": 10.0
}
|
Disqualifying_Properties |
array of strings |
NA |
NA |
[] |
A list of IndividualProperty key:value pairs that cause an intervention to be aborted (persistent interventions will stop being distributed to individuals with these values). See NodeProperties and IndividualProperties parameters for more information. Generally used to control the flow of health care access. For example, to prevent the same individual from accessing health care via two different routes at the same time. |
{
"Disqualifying_Properties": [
"InterventionStatus:LostForever"
]
}
|
Dont_Allow_Duplicates |
boolean |
0 |
1 |
0 |
If an individual’s container has an intervention, set to true (1) to prevent them from receiving another copy of the intervention. Supported by all intervention classes. |
{
"Dont_Allow_Duplicates": 0
}
|
Efficacy_Is_Multiplicative |
boolean |
0 |
1 |
1 |
The overall vaccine efficacy when individuals receive more than one vaccine. When set to true (1), the vaccine efficacies are multiplied together; when set to false (0), the efficacies are additive. |
{
"Intervention_Config": {
"class": "SimpleVaccine",
"Cost_To_Consumer": 10,
"Vaccine_Type": "AcquisitionBlocking",
"Vaccine_Take": 1,
"Efficacy_Is_Multiplicative": 0,
"Waning_Config": {
"class": "WaningEffectConstant",
"Initial_Effect": 0.3
}
}
}
|
Intervention_Name |
string |
NA |
NA |
NA |
The optional name used to refer to this intervention as a means to differentiate it from others that use the same class. |
{
"Intervention_Config": {
"class": "SimpleBoosterVaccine",
"Intervention_Name": "Tetanus booster shot"
}
}
|
New_Property_Value |
string |
NA |
NA |
NA |
An optional IndividualProperty key:value pair that will be assigned when the intervention is distributed. See NodeProperties and IndividualProperties parameters for more information. Generally used to indicate the broad category of health care cascade to which an intervention belongs to prevent individuals from accessing care through multiple pathways. For example, if an individual must already be taking a particular medication to be prescribed a new one. |
{
"New_Property_Value": "InterventionStatus:None"
}
|
Prime_Effect |
float |
0 |
1 |
1 |
Specifies the priming effect on [acquisition/transmission/mortality] immunity for naive individuals (without natural or vaccine-derived immunity). |
{
"Intervention_Config": {
"Cost_To_Consumer": 10.0,
"Vaccine_Take": 1,
"Vaccine_Type": "MortalityBlocking",
"Prime_Effect": 0.25,
"Boost_Effect": 0.45,
"Boost_Threshold": 0.0,
"Waning_Config": {
"Box_Duration": 10,
"Initial_Effect": 1,
"class": "WaningEffectBox"
},
"class": "SimpleBoosterVaccine"
}
}
|
Vaccine_Take |
float |
0 |
1 |
1 |
The rate at which delivered vaccines will successfully stimulate an immune response and achieve the desired efficacy. For example, if it is set to 0.9, there will be a 90 percent chance that the vaccine will start with the specified efficacy, and a 10 percent chance that it will have no efficacy at all. |
{
"Intervention_Config": {
"class": "SimpleVaccine",
"Cost_To_Consumer": 10,
"Vaccine_Type": "AcquisitionBlocking",
"Vaccine_Take": 1,
"Efficacy_Is_Multiplicative": 0,
"Waning_Config": {
"class": "WaningEffectConstant",
"Initial_Effect": 0.3
}
}
}
|
Vaccine_Type |
enum |
NA |
NA |
Generic |
The type of vaccine to distribute in a vaccine intervention. Possible values are:
|
{
"Intervention_Config": {
"class": "SimpleVaccine",
"Cost_To_Consumer": 10,
"Vaccine_Type": "AcquisitionBlocking",
"Vaccine_Take": 1,
"Efficacy_Is_Multiplicative": 0,
"Waning_Config": {
"class": "WaningEffectConstant",
"Initial_Effect": 0.3
}
}
}
|
Waning_Config |
JSON object |
NA |
NA |
NA |
The configuration of how the intervention efficacy wanes over time. Specify how this effect decays over time using one of the Waning effect classes. |
{
"Waning_Config": {
"Box_Duration": 3650,
"Initial_Effect": 1,
"class": "WaningEffectBox"
}
}
|
UsageDependentBednet (malaria)¶
The UsageDependentBednet intervention class is similar to SimpleBednet, as it distributes insecticide-treated nets to individuals in the simulation. However, bednet ownership and bednet usage are distinct in this intervention. As in SimpleBednet, net ownership is configured through the demographic coverage, and the blocking and killing rates of mosquitoes are time-dependent. Use of bednets is age-dependent and can vary seasonally. Once a net has been distributed to someone, the net usage is determined by the product of the seasonal and age-dependent usage probabilities until the net-retention counter runs out, and the net is discarded.
Parameter
Data type
Minimum
Maximum
Default
Description
Example
Blocking_Config
JSON object
NA
NA
NA
Configures the rate of blocking for indoor mosquito feeds on individuals with an ITN. Specify how this effect decays over time using one of the Waning effect classes.
Cost_To_Consumer
float
0
999999
3.75
The unit cost per bednet (unamortized)
Discard_Event
enum
NA
NA
“”
The event that is broadcast when an individual discards their bed net, either by replacing an existing net or due to the expiration timer. See Event list for possible values.
Disqualifying_Properties
array of strings
NA
NA
[]
A list of IndividualProperty key:value pairs that cause an intervention to be aborted (persistent interventions will stop being distributed to individuals with these values). See NodeProperties and IndividualProperties parameters for more information. Generally used to control the flow of health care access. For example, to prevent the same individual from accessing health care via two different routes at the same time.
Dont_Allow_Duplicates
boolean
0
1
0
If an individual’s container has an intervention, set to true (1) to prevent them from receiving another copy of the intervention. Supported by all intervention classes.
Expiration_Period_Constant
float
0
3.40282E+38
6
The expiration period to use for all bednets when Expiration_Period_Distribution is set to CONSTANT_DISTRIBUTION.
Expiration_Period_Distribution
enum
NA
NA
NOT_INITIALIZED
The distribution type to use for assigning the expiration period to a usage-dependent bednet. Each assigned value is a random draw from the distribution.
Possible values are:
- NOT_INITIALIZED
No distribution set.
- CONSTANT_DISTRIBUTION
Use the same value for each individual. Set Expiration_Period_Constant.
- UNIFORM_DISTRIBUTION
Use a uniform distribution with a given minimum and maximum. Set Expiration_Period_Max and Expiration_Period_Min.
- GAUSSIAN_DISTRIBUTION
The distribution is Gaussian (or normal). Set Expiration_Period_Gaussian_Mean and Expiration_Period_Gaussian_Std_Dev.
- EXPONENTIAL_DISTRIBUTION
The distribution is exponential with a given mean. Set Expiration_Period_Exponential.
- WEIBULL_DISTRIBUTION
Use a Weibull distribution with a given shape and scale. Set Expiration_Period_Kappa and Expiration_Period_Lambda.
- LOG_NORMAL_DISTRIBUTION
Use a log-normal distribution with a given mean and width. Set Expiration_Period_Log_Normal_Mean and Expiration_Period_Log_Normal_Width.
- POISSON_DISTRIBUTION
Use a Poisson distribution with a given mean. Set Expiration_Period_Poisson_Mean.
- DUAL_CONSTANT_DISTRIBUTION
Use a distribution where some individuals are set to a value of zero and the rest to a given value. Set Expiration_Period_Proportion_0 and Peak_2_Value. This distribution does not use the parameters set for CONSTANT_DISTRIBUTION.
- DUAL_EXPONENTIAL_DISTRIBUTION
Use two exponential distributions with given means. Set Expiration_Period_Mean_1, Expiration_Period_Mean_2, and Expiration_Period_Proportion_1. This distribution does not use the parameters set for EXPONENTIAL_DISTRIBUTION.
Expiration_Period_Exponential
float
0
3.40282E+38
6
The mean of the expiration period when Expiration_Period_Distribution is set to EXPONENTIAL_DISTRIBUTION.
Expiration_Period_Gaussian_Mean
float
0
3.40282E+38
6
The mean of the expiration period when Expiration_Period_Distribution is set to GAUSSIAN_DISTRIBUTION.
Expiration_Period_Gaussian_Std_Dev
float
1.17549E-38
3.40282E+38
1
The standard deviation of the expiration period when Expiration_Period_Distribution is set to GAUSSIAN_DISTRIBUTION.
Expiration_Period_Kappa
float
1.17549E-38
3.40282E+38
1
The shape value for the expiration period when Expiration_Period_Distribution is set to WEIBULL_DISTRIBUTION.
Expiration_Period_Lambda
float
1.17549E-38
3.40282E+38
1
The scale value for the expiration period when Expiration_Period_Distribution is set to WEIBULL_DISTRIBUTION.
Expiration_Period_Log_Normal_Mu
float
-3.40282e+38
3.40282E+38
6
The mean of the expiration period when Expiration_Period_Distribution is set to LOG_NORMAL_DISTRIBUTION.
Expiration_Period_Log_Normal_Sigma
float
-3.40282e+38
3.40282E+38
1
The width of the expiration period when Expiration_Period_Distribution is set to LOG_NORMAL_DISTRIBUTION.
Expiration_Period_Max
float
0
3.40282E+38
1
The maximum expiration period when Expiration_Period_Distribution is set to UNIFORM_DISTRIBUTION.
Expiration_Period_Mean_1
float
1.17549E-38
3.40282E+38
1
The mean of the first exponential distribution.
Expiration_Period_Mean_2
float
1.17549E-38
3.40282E+38
1
The mean of the second exponential distribution.
Expiration_Period_Min
float
0
3.40282E+38
0
The minimum expiration period when Expiration_Period_Distribution is set to UNIFORM_DISTRIBUTION.
Expiration_Period_Peak_2_Value
float
0
3.40282E+38
1
The expiration period value to assign to the remaining bednets when Expiration_Period_Distribution is set to DUAL_CONSTANT_DISTRIBUTION.
Expiration_Period_Poisson_Mean
float
0
3.40282E+38
6
The mean of the expiration period when Expiration_Period is set to POISSON_DISTRIBUTION.
Expiration_Period_Proportion_0
float
0
1
1
The proportion of bednets to assign a value of zero days until expiration when Expiration_Period_Distribution is set to DUAL_CONSTANT_DISTRIBUTION.
Expiration_Period_Proportion_1
float
0
1
1
The proportion of bednets in the first exponential distribution.
Intervention_Name
string
NA
NA
NA
The optional name used to refer to this intervention as a means to differentiate it from others that use the same class.
Killing_Config
JSON object
NA
NA
NA
The configuration of the rate at which mosquitoes die, conditional on a successfully blocked feed. Specify how this effect decays over time using one of the Waning effect classes.
New_Property_Value
string
NA
NA
NA
An optional IndividualProperty key:value pair that will be assigned when the intervention is distributed. See NodeProperties and IndividualProperties parameters for more information. Generally used to indicate the broad category of health care cascade to which an intervention belongs to prevent individuals from accessing care through multiple pathways. For example, if an individual must already be taking a particular medication to be prescribed a new one.
Received_Event
enum
NA
NA
“”
This parameter broadcasts when a new net is received, either the first net or a replacement net. See Event list for possible values.
Usage_Config_List
array of JSON objects
NA
NA
NA
The list of WaningEffects whose effects are multiplied together to get the usage effect. Specify how this effect decays over time using one of the Waning effect classes.
Using_Event
enum
NA
NA
NA
This parameter broadcasts each time step in which a bed net is used. See Event list for possible values.
Malaria model¶
Several habitat parameters in the malaria model have been upgraded, creating more flexibility in the model and enabling the user to have more control over habitat customization. These changes allow the model to more accurately capture real-world habitat availability and how it affects different mosquito species.
- LINEAR_SPLINE habitat type
This new option under Larval_Habitat_Types increases model customization by allowing the user to specify an arbitrary functional form (derived from data) for larval habitat availability throughout the year, instead of relying on climatological parameters such as rainfall or temperature. For more information, see Larval habitat parameters.
- LarvalHabitatMultiplier by species
This new feature in demographics allows larval habitat availability to be modified independently for each species sharing a particular habitat type. Prior versions of EMOD applied the same modifier to all species within a shared habitat; this upgrade enables you to apply modifiers to individual species within a habitat. For more information, see NodeAttributes parameters.
- ScaleLarvalHabitat by species
This new intervention enables species-specific effects of habitat interventions within shared habitat types, such that habitat availability is modified on a per-species level.
- Breaking changes
PIECEWISE_MONTHLY has been changed to LINEAR_SPLINE.